Job Description - "Experience:

Experience in data analysis or a related field, with a strong background in statistical analysis, data mining, and data visualization.

Responsibilities:

1.           Extract and analyze transactional data and bug reports from JIRA, utilizing SQL, Python, R, or similar data extraction and analysis tools.

2.           Develop, test, and refine hypotheses based on extracted data, aimed at driving efficiency gains and quality improvements within the organization.

3.           Perform comprehensive reviews of current data states to identify gaps and opportunities for enhancing data collection, storage, and analysis processes.

4.           Design and implement additional data elements and structures to support advanced data collection and analytical methodologies, ensuring data integrity and availability.

5.           Build robust and complex data taxonomy strategies around existing data stores, enabling flexible and insightful analysis and reporting to support decision-making processes across various departments.

6.           Collaborate with cross-functional teams to understand data needs and deliver actionable insights.

7.           Create and maintain documentation for data analysis processes, data models, and analysis findings, facilitating knowledge sharing and process improvement.

8.           Leverage industry trends and advancements in data analysis tools and methodologies, incorporating best practices into daily work to enhance outcomes.

 

Knowledge & Skills:

1.           Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.

2.           Proficient in data analysis tools and programming languages such as SQL, Python, R, or similar.

3.           Experience with data visualization tools like Tableau, Power BI, or similar, to create impactful reports and dashboards.

4.           Deep understanding of data warehousing, data cleaning, and data preprocessing techniques.

5.           Knowledge of statistical modeling, predictive analysis, and data mining techniques.

6.           Ability to work independently and collaboratively in a fast-paced environment, managing multiple projects and deadlines effectively.

7.           Excellent problem-solving skills and the ability to think critically to overcome analytical challenges.

8.           Strong communication skills, capable of conveying complex data insights to non-technical stakeholders in a clear and concise manner."

interview Transcript - "WEBVTT

00:00:00.000 --> 00:00:02.060
<v Patty Shaw>Do you have any other questions before we start?</v>

00:00:03.270 --> 00:00:05.250
<v Sohail Pathan>No, I don't have any other questions.</v>

00:00:11.950 --> 00:00:12.400
<v Patty Shaw>OK. Yeah.</v>

00:00:05.260 --> 00:00:12.500
<v Sohail Pathan>I am ready to go into a purpose quick shot technical dive whenever you are ready.</v>

00:00:13.990 --> 00:00:14.250
<v Patty Shaw>Ready.</v>

00:00:15.640 --> 00:00:24.130
<v Sohail Pathan>Alright, so uh, I have gone through your resume and I see that you have used SQL and I think you've also used Python, right?</v>

00:00:25.990 --> 00:00:30.970
<v Patty Shaw>I use Python a little bit, but it wasn't an expensive.</v>

00:00:31.990 --> 00:00:32.580
<v Sohail Pathan>OK.</v>

00:00:32.640 --> 00:00:42.340
<v Sohail Pathan>So can you provide me examples based on your hands on experience with SQL and Python or any other data extraction or analysis tool?</v>

00:00:42.510 --> 00:00:43.140
<v Sohail Pathan>What?</v>

00:00:43.550 --> 00:00:44.800
<v Sohail Pathan>Which one do you prefer?</v>

00:00:44.810 --> 00:00:48.690
<v Sohail Pathan>And for the large datasets and why is that your preference?</v>

00:00:49.950 --> 00:01:00.620
<v Patty Shaw>OK, I personally most prefer a sequel cause it's a it's a language that all of the companies and all the teams I've worked on used.</v>

00:01:00.930 --> 00:01:13.560
<v Patty Shaw>And so I could use that to easily communicate with more of my coworkers throughout the different organizations I did like when Python, became a big thing, I could go in and learn it.</v>

00:01:20.790 --> 00:01:21.070
<v Sohail Pathan>Umm.</v>

00:01:13.570 --> 00:01:24.830
<v Patty Shaw>And I did try to incorporate it with what I was already doing at JP Morgan Chase, but I discovered that like we, you know, as a organization.</v>

00:01:24.840 --> 00:01:35.130
<v Patty Shaw>We talked about wanting to use Python, but and even though some people have experience with Python, at the end of the day a lot of times we revert back to SQL and then we revert back to Excel.</v>

00:01:35.460 --> 00:01:38.190
<v Patty Shaw>So ended up not really using it.</v>

00:01:39.760 --> 00:01:40.000
<v Sohail Pathan>OK.</v>

00:01:39.370 --> 00:01:41.740
<v Patty Shaw>Umm, so for sequel?</v>

00:01:42.830 --> 00:01:56.190
<v Patty Shaw>I've used it basically in almost every row I've had started with business system analyst pulling data from auto loan origination systems in order to support.</v>

00:01:58.260 --> 00:02:03.520
<v Patty Shaw>Like to confirm the issues that our call center employees were seeing.</v>

00:02:04.270 --> 00:02:11.660
<v Patty Shaw>Or some of the product managers are saying and from there to pull data to support that.</v>

00:02:11.670 --> 00:02:12.180
<v Patty Shaw>OK.</v>

00:02:12.250 --> 00:02:19.880
<v Patty Shaw>Well, kind of like do a quick through cost analysis before we have to point with developers to make changes to the systems.</v>

00:02:20.210 --> 00:02:55.590
<v Patty Shaw>And so I will use SQL in order to see if it's like a data cleaning issue and if that was an issue then I will reach out to the database admin for her to change it on her side and then do more testing to see if the issue is resolved and if so then I will, you know close the ticket so our developers don't have to spend time on developing enhancements and or if there's issues related to the system then I will enter it into our fast track pipeline.</v>

00:02:55.600 --> 00:03:11.570
<v Patty Shaw>Thought I was running for a few years before and so we will quickly do enhancement with collaboration with the India team, with Infosys and Cognizant, and then we will also.</v>

00:03:13.820 --> 00:03:35.070
<v Patty Shaw>Work on side with the employees there and make those enhancement and then do the testing with the end users to make sure that they understand the enhancement and they are OK with how it looks and it's intuitive to their day-to-day usage.</v>

00:03:35.330 --> 00:03:37.310
<v Patty Shaw>So that's one example of using SQL.</v>

00:03:38.180 --> 00:03:39.450
<v Patty Shaw>What JP Morgan Chase?</v>

00:03:39.460 --> 00:03:45.100
<v Patty Shaw>I used SQL in order to pull data and like mainly do data cleansing.</v>

00:03:47.180 --> 00:03:51.790
<v Patty Shaw>Well, data viewing in order to find what is wrong with the data and then do data cleansing.</v>

00:03:51.800 --> 00:03:54.010
<v Patty Shaw>And I also use altrix.</v>

00:03:54.140 --> 00:04:19.790
<v Patty Shaw>That's when I first got my ultra certification and so I use Ultra AKS to ultimate the workflows into regular reports that so prior to me and my coworker starting using Alteryx on that, all of Excel, she's coming statically and then people will have to like extract it and then email it to you.</v>

00:04:19.800 --> 00:04:25.890
<v Patty Shaw>And then, like, feel the emails, sometimes the files will get corrupted and then you can open it or it's missing data.</v>

00:04:26.260 --> 00:04:36.170
<v Patty Shaw>So what happened is that we found all the archived copies and then we went through them and see what is wrong with the data and make sure that everything was OK.</v>

00:04:36.180 --> 00:04:58.700
<v Patty Shaw>But then we discovered that we have to do a lot of Data cleans it, so then together my coworker and I worked on different altreps workflows to automate that part and then eventually we make new addition like, yeah, new versions of the previous regular reports.</v>

00:04:59.900 --> 00:05:00.120
<v Sohail Pathan>OK.</v>

00:04:59.030 --> 00:05:08.860
<v Patty Shaw>And then we make sure that you know things flow directly from the from the database, from a data sources into our tricks, and then into the new reports.</v>

00:05:09.310 --> 00:05:22.940
<v Patty Shaw>And then we also create a new tableau dashboards from there in order to support what the management wanted as a new improvement to our organization.</v>

00:05:25.090 --> 00:05:25.440
<v Patty Shaw>Umm.</v>

00:05:25.370 --> 00:05:25.630
<v Sohail Pathan>OK.</v>

00:05:25.530 --> 00:05:50.250
<v Patty Shaw>And then with my current company, umm, after the part that I mentioned before about a data entry part which took months to complete 1 coworker and I started working on setting up like SQL query for the team to use because not everyone within the company was tech savvy.</v>

00:05:50.640 --> 00:05:57.590
<v Patty Shaw>And so we're trying to train people a little bit about how they could use our SQL queries and look at the database themselves.</v>

00:05:57.970 --> 00:05:59.260
<v Patty Shaw>And then come together.</v>

00:05:59.270 --> 00:06:08.690
<v Patty Shaw>We also set up Altrix workflows and some like easier to use, not too complex dashboards full of management, and the Co owners.</v>

00:06:10.600 --> 00:06:11.120
<v Sohail Pathan>Nice.</v>

00:06:15.210 --> 00:06:15.420
<v Patty Shaw>Yeah.</v>

00:06:11.360 --> 00:06:20.640
<v Sohail Pathan>So in terms of large datasets with regards to robustness and speed, what do you think is more optimal?</v>

00:06:30.440 --> 00:06:30.700
<v Sohail Pathan>Umm.</v>

00:06:24.260 --> 00:06:40.840
<v Patty Shaw>So when it comes to super large datasets like what I experienced with JP Morgan Chase and Dey, to me speed is the most important over the over, like the esthetics over the different views and all that.</v>

00:06:48.500 --> 00:06:48.670
<v Sohail Pathan>Right.</v>

00:06:40.950 --> 00:07:00.380
<v Patty Shaw>So we like me and my one partner, we always try to design based on speed, cause a lot of times our our mortgage writers or our other users or call center employees, they're on the web and they have to like quickly support their clients.</v>

00:07:00.730 --> 00:07:06.760
<v Patty Shaw>And when the dashboard or like taking a minute to run, it feels like forever to them.</v>

00:07:07.030 --> 00:07:16.610
<v Patty Shaw>So we try to make sure speed is optimized so it doesn't have that leg where they're like filling their thumbs with their clients.</v>

00:07:16.620 --> 00:07:17.810
<v Patty Shaw>And they're like, ohh sorry.</v>

00:07:17.820 --> 00:07:19.050
<v Patty Shaw>Give me a moment.</v>

00:07:19.100 --> 00:07:20.150
<v Patty Shaw>While a dashboard run.</v>

00:07:22.170 --> 00:07:25.910
<v Sohail Pathan>OK, so which tool would be more optimal in this case?</v>

00:07:28.770 --> 00:07:29.280
<v Patty Shaw>Umm.</v>

00:07:31.930 --> 00:07:33.260
<v Patty Shaw>Data cleansing?</v>

00:07:33.370 --> 00:07:37.280
<v Patty Shaw>Umm, beforehand and like minimizing the data set?</v>

00:07:37.370 --> 00:07:42.160
<v Patty Shaw>That's really needed for the dashboard and make sure it's built in layers.</v>

00:07:42.170 --> 00:07:53.550
<v Patty Shaw>So kind of like give one quick high level and then like filter the data down into the details as they are needed but not put all the detail onto the main dashboard.</v>

00:07:55.430 --> 00:07:55.730
<v Sohail Pathan>OK.</v>

00:07:58.760 --> 00:08:06.800
<v Sohail Pathan>How do you handle data integrity and reliability when uh, working with JIRA and big transactional data?</v>

00:08:09.990 --> 00:08:11.100
<v Patty Shaw>Data integrity.</v>

00:08:14.980 --> 00:08:26.010
<v Patty Shaw>I was a part of a team that was like making sure only people who need it access get access and so they will have to give U.S.</v>

00:08:26.020 --> 00:08:39.600
<v Patty Shaw>Business statements about why they needed access to certain dashboards to certain data sources, or they also have to support what are their credentials to add data to the data sources?</v>

00:08:40.560 --> 00:09:17.270
<v Patty Shaw>Umm so I from my experience I think it's important to kind of like monitor and control but Assets that people have and like after a while if they haven't been using those datasets or umm the dashboards we remove them periodically so it doesn't cause as much to get all the licenses and then and make sure that we don't have like open ends loose ends like if people move on to a different row they cannot come back in and look at data that they don't have.</v>

00:09:17.360 --> 00:09:18.820
<v Patty Shaw>They shouldn't have access to anymore.</v>

00:09:21.160 --> 00:09:21.520
<v Sohail Pathan>OK.</v>

00:09:22.860 --> 00:09:25.000
<v Sohail Pathan>Ah, what are multimodal datasets?</v>

00:09:27.540 --> 00:09:34.550
<v Patty Shaw>Uh, multimodal datasets are datasets that come from different sources.</v>

00:09:36.070 --> 00:09:37.110
<v Patty Shaw>Umm and.</v>

00:09:38.720 --> 00:09:39.520
<v Patty Shaw>They can be.</v>

00:09:42.300 --> 00:09:48.800
<v Patty Shaw>Like merge and combined and then make into whatever you need to present.</v>

00:09:50.260 --> 00:09:58.120
<v Sohail Pathan>So we won't there be integrity and reliability issues in this and how do you think would you solve them?</v>

00:10:08.580 --> 00:10:08.860
<v Sohail Pathan>Umm.</v>

00:09:59.810 --> 00:10:16.080
<v Patty Shaw>So when I was working on the war war Agage side of JP Morgan Chase, some of the reports that have data from different concept of visions within a mortgage line of business.</v>

00:10:16.950 --> 00:10:26.160
<v Patty Shaw>And sometimes I have to work with people in compliance to make sure, you know, look, data are correct.</v>

00:10:26.640 --> 00:10:27.070
<v Patty Shaw>Umm.</v>

00:10:27.680 --> 00:10:52.280
<v Patty Shaw>And then sometimes I have to work with people from call centers and sometimes with like the underwriters to make sure that what they are entering is related and to make sure that they're following the best practices and also work with developers to make sure that whatever they're capturing from our system has been updated to the new guidelines.</v>

00:10:52.730 --> 00:11:00.150
<v Patty Shaw>And so in that process, it's making sure that the integrity and the data are the data integrity is correct.</v>

00:11:04.640 --> 00:11:05.030
<v Sohail Pathan>OK.</v>

00:11:06.560 --> 00:11:09.130
<v Sohail Pathan>So are.</v>

00:11:12.180 --> 00:11:13.340
<v Sohail Pathan>Let's move on.</v>

00:11:17.160 --> 00:11:17.650
<v Sohail Pathan>Can you?</v>

00:11:17.830 --> 00:11:27.290
<v Sohail Pathan>Can you share a little bit of on your experience about data visualization tools like Tableau or Power BI?</v>

00:11:29.990 --> 00:11:33.120
<v Patty Shaw>So ohh, I've mainly used Tableau.</v>

00:11:33.390 --> 00:11:45.600
<v Patty Shaw>I did take a course in Power BI back end 2019-2020 time frame, but all organizations I've worked with, they always they were already on Tableau.</v>

00:11:57.110 --> 00:11:57.380
<v Sohail Pathan>Umm.</v>

00:11:45.930 --> 00:11:58.140
<v Patty Shaw>So I just continue with the table trend and so one of the biggest projects that I have to work on was the JIRA data set with JP Morgan Chase.</v>

00:11:58.510 --> 00:12:06.840
<v Patty Shaw>So that was when my team was moving from the Cao organization into the Agile transformation organization.</v>

00:12:07.270 --> 00:12:23.810
<v Patty Shaw>And so it was like a brand new business initiative and my one partner and I were in charge of all the tablet Ward and also making sure all of data or floating through correctly, it wasn't identified before where the data will come from.</v>

00:12:24.080 --> 00:12:37.090
<v Patty Shaw>It wasn't identified who will get access to the JIRA, dataset and so as it turns out, within Chase here data set was managed by this JIRA admin who is not even in our organization.</v>

00:12:37.480 --> 00:12:45.780
<v Patty Shaw>And so it took us like a lot of going around, like contacting different people, contacting the tableau community.</v>

00:12:46.520 --> 00:12:50.440
<v Patty Shaw>Uh Center of Excellence contact in different uh.</v>

00:12:51.290 --> 00:12:59.990
<v Patty Shaw>Point of contact that we have in our personal contacts and to identify that, first of all, there's a row such as that.</v>

00:13:00.070 --> 00:13:09.340
<v Patty Shaw>Who takes care of all a JIRA administration within JP Morgan Chase and that person was the only person who could contact Shiro.</v>

00:13:10.230 --> 00:13:14.700
<v Patty Shaw>So by contract, we cannot just reach out to JIRA for support like that.</v>

00:13:15.160 --> 00:13:15.480
<v Sohail Pathan>Right.</v>

00:13:14.710 --> 00:13:17.870
<v Patty Shaw>We have to go through that first and then so.</v>

00:13:19.870 --> 00:13:21.420
<v Patty Shaw>Like it took a while to figure it out.</v>

00:13:21.430 --> 00:13:26.040
<v Patty Shaw>He existed and to uh build up report and let him know what is our issue.</v>

00:13:26.290 --> 00:13:37.300
<v Patty Shaw>And So what we discover is that well, management came to us and they say they want a clear view into how our juror tickets are moving along.</v>

00:13:37.720 --> 00:13:43.770
<v Patty Shaw>They want to use that in order to monitor developer efficiency and productivity.</v>

00:13:44.850 --> 00:13:45.120
<v Sohail Pathan>Umm.</v>

00:13:44.320 --> 00:13:59.560
<v Patty Shaw>So my coworker and I, we work together to make sure that we get access to Liju a data, and that also took several months because of all the loops that you have to work through and all the different departments you have to contact.</v>

00:14:00.090 --> 00:14:00.430
<v Sohail Pathan>Right.</v>

00:13:59.830 --> 00:14:13.280
<v Patty Shaw>So eventually we finally get access to the JIRA data and then we discover that a lot of times people don't enter everything that is required for us to do analysis that we that management has requested.</v>

00:14:13.550 --> 00:14:20.080
<v Patty Shaw>So then it also took some time to work with different developer teams.</v>

00:14:20.710 --> 00:14:44.120
<v Patty Shaw>People like with developers and the team leads to communicate to them what kind of data are necessary, how they should enter it, and we also have to design different categories different like level details and create examples of, UM, different entries on different kinds of JIRA project types.</v>

00:14:44.480 --> 00:14:56.160
<v Patty Shaw>So make sure that people understand what they need to do, and then we also have to respectively go back to prior Jura tickets that have not been closed yet in order to add those details.</v>

00:14:56.560 --> 00:15:04.610
<v Patty Shaw>So yeah, but eventually we, after all of data, catch up data cleansing, data merging.</v>

00:15:05.020 --> 00:15:11.770
<v Patty Shaw>We were able to come up with Tableau Dashboard that shows on a high level.</v>

00:15:12.130 --> 00:15:14.650
<v Patty Shaw>What are all open tickets at the moment?</v>

00:15:15.500 --> 00:15:47.210
<v Patty Shaw>Which tickets closed in the last Sprint and then also we could like the user whether it's management or the team leaves or the individual developers they could drill down into the details of what this particular JIRA ticket like how long it has been open, who was the source like, which department, who was the point of contact on both ends and then eventually they could draw it down all the way down to opening up the exact your ticket.</v>

00:15:47.660 --> 00:15:49.250
<v Patty Shaw>Just see for themselves.</v>

00:15:49.300 --> 00:15:55.300
<v Patty Shaw>Like whatever other detail they want, or they may want to see from which your system.</v>

00:15:57.270 --> 00:15:57.740
<v Sohail Pathan>Nice.</v>

00:15:57.930 --> 00:16:02.400
<v Sohail Pathan>So I see that you're quite familiar and you've worked a lot on Tableau.</v>

00:16:02.710 --> 00:16:03.980
<v Sohail Pathan>How about power BI?</v>

00:16:03.990 --> 00:16:05.830
<v Sohail Pathan>Do you think you're comfortable with power BI?</v>

00:16:07.980 --> 00:16:11.810
<v Patty Shaw>So it sounds like HP uses power BI predominantly.</v>

00:16:13.550 --> 00:16:13.930
<v Sohail Pathan>Uh.</v>

00:16:14.050 --> 00:16:14.480
<v Patty Shaw>Uh.</v>

00:16:15.990 --> 00:16:17.810
<v Sohail Pathan>They use power BI predominantly.</v>

00:16:19.310 --> 00:16:19.690
<v Patty Shaw>OK.</v>

00:16:20.480 --> 00:16:24.510
<v Patty Shaw>Umm, I could like before the start day.</v>

00:16:24.520 --> 00:16:35.280
<v Patty Shaw>I could definitely brush up on my skills with power BI and then so that ties into the question of what is like expectation of me for the 1st 90 days on those row.</v>

00:16:39.150 --> 00:16:39.350
<v Sohail Pathan>So.</v>

00:16:39.310 --> 00:16:41.890
<v Patty Shaw>And yeah, go ahead.</v>

00:16:41.430 --> 00:16:41.980
<v Sohail Pathan>Yeah, go ahead.</v>

00:16:43.450 --> 00:16:53.530
<v Patty Shaw>Ohh, I was just gonna say like that depends, you know, like me, I could get ready beforehand, but I also, you know, depending on what was expected and the 1st 80 days.</v>

00:16:53.700 --> 00:17:02.040
<v Patty Shaw>If there's like some time for me to catch up, then I will go in and build some simple dashboards myself and power BI to get familiarized with it.</v>

00:17:03.420 --> 00:17:03.840
<v Sohail Pathan>OK.</v>

00:17:03.850 --> 00:17:04.800
<v Sohail Pathan>But as of today?</v>

00:17:05.090 --> 00:17:08.310
<v Sohail Pathan>Ohh, what is your confidence level in Power BI?</v>

00:17:10.660 --> 00:17:10.970
<v Patty Shaw>Umm.</v>

00:17:12.980 --> 00:17:16.070
<v Patty Shaw>I wouldn't work as fast on the as what tableau.</v>

00:17:18.630 --> 00:17:21.670
<v Patty Shaw>So if on a scale of 10, probably is 6.</v>

00:17:23.970 --> 00:17:24.660
<v Sohail Pathan>That's nice.</v>

00:17:24.890 --> 00:17:26.800
<v Sohail Pathan>So let's do one thing.</v>

00:17:27.560 --> 00:17:34.390
<v Sohail Pathan>Let me share you one link in the chat and you can share your screen and open up that link.</v>

00:17:36.100 --> 00:17:36.340
<v Patty Shaw>OK.</v>

00:17:38.190 --> 00:17:38.760
<v Patty Shaw>Umm.</v>

00:17:45.450 --> 00:17:46.410
<v Patty Shaw>Oh, is it already in there?</v>

00:17:47.770 --> 00:17:51.090
<v Sohail Pathan>I'll share the link once you start sharing your screen.</v>

00:17:52.240 --> 00:17:55.720
<v Patty Shaw>Ah, OK, uh, let me figure out how to share my screen one second.</v>

00:18:02.220 --> 00:18:02.680
<v Patty Shaw>Here.</v>

00:17:58.370 --> 00:18:03.620
<v Sohail Pathan>If you're from browser, there should be a button and the center of your toolbar.</v>

00:18:04.850 --> 00:18:06.530
<v Patty Shaw>Yeah, share screen.</v>

00:18:08.370 --> 00:18:11.030
<v Patty Shaw>I'm tired window.</v>

00:18:10.720 --> 00:18:14.610
<v Sohail Pathan>Browser just a browser window or the whole screen?</v>

00:18:14.620 --> 00:18:15.980
<v Sohail Pathan>Anything that you're comfortable with?</v>

00:18:17.920 --> 00:18:18.310
<v Patty Shaw>OK.</v>

00:18:18.360 --> 00:18:22.280
<v Patty Shaw>Ohh Shirley entire screen then OK sharing.</v>

00:18:21.030 --> 00:18:22.590
<v Sohail Pathan>You think that you're comfortable with?</v>

00:18:22.600 --> 00:18:22.970
<v Sohail Pathan>That's fine.</v>

00:18:24.050 --> 00:18:24.630
<v Patty Shaw>Doesn't show up.</v>

00:18:25.790 --> 00:18:26.900
<v Sohail Pathan>Yes, it did show.</v>

00:18:27.010 --> 00:18:28.660
<v Patty Shaw>And fabulous.</v>

00:18:29.090 --> 00:18:31.140
<v Sohail Pathan>I have sent you a link.</v>

00:18:31.250 --> 00:18:36.480
<v Sohail Pathan>Uh, you can go to the chat box and see if you have received that link.</v>

00:18:38.580 --> 00:18:38.750
<v Patty Shaw>And.</v>

00:18:36.540 --> 00:18:39.170
<v Sohail Pathan>Yeah, you can simply click on it.</v>

00:18:39.180 --> 00:18:40.330
<v Sohail Pathan>It will open up in a new tab.</v>

00:18:46.670 --> 00:18:46.850
<v Sohail Pathan>Yeah.</v>

00:18:42.730 --> 00:18:47.550
<v Patty Shaw>Ohh but I didn't copy choirs I magine.</v>

00:18:47.710 --> 00:18:57.360
<v Sohail Pathan>So this is an interesting game that I like to try out and I would like you to try it out with the four number of disks.</v>

00:18:57.470 --> 00:19:02.300
<v Sohail Pathan>So just click on upward arrow and it will increase the number of disks.</v>

00:19:09.660 --> 00:19:10.690
<v Sohail Pathan>Yes, yes.</v>

00:19:04.720 --> 00:19:12.850
<v Patty Shaw>OK, we're trying to move to tower three and Tower three is the one on the right hand side, right, OK, uh.</v>

00:19:12.190 --> 00:19:14.140
<v Sohail Pathan>You have to change the number to four.</v>

00:19:14.190 --> 00:19:15.810
<v Sohail Pathan>Number of disks should be 4.</v>

00:19:16.800 --> 00:19:17.600
<v Patty Shaw>Out to four.</v>

00:19:18.160 --> 00:19:19.670
<v Sohail Pathan>Yeah, that's awesome.</v>

00:19:17.900 --> 00:19:20.680
<v Patty Shaw>OK, Ohh that does make it harder.</v>

00:19:20.880 --> 00:19:21.160
<v Patty Shaw>OK.</v>

00:19:22.140 --> 00:19:22.490
<v Patty Shaw>Umm.</v>

00:19:23.750 --> 00:19:26.780
<v Patty Shaw>Minimum lose 15 so 1/2.</v>

00:19:28.540 --> 00:19:28.760
<v Patty Shaw>OK.</v>

00:19:30.870 --> 00:19:37.030
<v Patty Shaw>So I just OK to we.</v>

00:19:40.160 --> 00:19:49.690
<v Patty Shaw>Or minimum of 15, does that mean it will take the best player 15 moves to complete it or like?</v>

00:19:49.070 --> 00:19:50.180
<v Sohail Pathan>No, there isn't.</v>

00:19:50.460 --> 00:19:54.290
<v Sohail Pathan>For an average player, you can probably do it in less.</v>

00:19:56.170 --> 00:19:57.350
<v Patty Shaw>Oh, OK.</v>

00:19:59.400 --> 00:20:03.100
<v Patty Shaw>I should put it on the second one. Umm.</v>

00:20:05.720 --> 00:20:08.400
<v Patty Shaw>Yeah, we still few moves.</v>

00:20:24.450 --> 00:20:25.000
<v Patty Shaw>OK.</v>

00:20:25.090 --> 00:20:27.940
<v Patty Shaw>Yeah, I should have started putting out the second tower.</v>

00:20:34.010 --> 00:20:35.040
<v Patty Shaw>Is it OK if I restart?</v>

00:20:36.630 --> 00:20:37.200
<v Sohail Pathan>That's fine.</v>

00:20:40.660 --> 00:20:41.260
<v Patty Shaw>Their tower.</v>

00:20:37.210 --> 00:20:42.650
<v Sohail Pathan>Let's consider your second R as your target one, yeah.</v>

00:20:42.180 --> 00:20:43.860
<v Patty Shaw>Uh, we're we're gonna consider it a second.</v>

00:20:45.520 --> 00:20:45.720
<v Sohail Pathan>Yeah.</v>

00:20:43.870 --> 00:20:48.460
<v Patty Shaw>Towers on 3rd towel like OK there.</v>

00:20:49.280 --> 00:20:50.070
<v Sohail Pathan>OK, awesome.</v>

00:20:52.690 --> 00:20:54.050
<v Sohail Pathan>You can stop your screen share.</v>

00:20:54.060 --> 00:20:54.510
<v Sohail Pathan>That's fine.</v>

00:20:55.480 --> 00:20:55.900
<v Patty Shaw>OK.</v>

00:20:56.870 --> 00:20:57.250
<v Patty Shaw>Umm.</v>

00:20:57.350 --> 00:20:59.130
<v Patty Shaw>Steph Curry's cool.</v>

00:21:00.550 --> 00:21:01.350
<v Patty Shaw>That's fun though.</v>

00:21:00.290 --> 00:21:03.110
<v Sohail Pathan>OK, now, uh, yeah.</v>

00:21:03.220 --> 00:21:04.800
<v Sohail Pathan>I just wanted to take it on a lighter note.</v>

00:21:07.380 --> 00:21:07.540
<v Patty Shaw>Yeah.</v>

00:21:06.660 --> 00:21:24.400
<v Sohail Pathan>All right, so describe me a situation where you would apply statistical modeling and predictive analysis or any other data mining technique to give some efficiency related metrics or efficiency related data.</v>

00:21:34.280 --> 00:21:34.500
<v Sohail Pathan>Umm.</v>

00:21:25.690 --> 00:21:57.930
<v Patty Shaw>OK, so I was in Taiwan for almost seven months prior to March 28th and so for my current company, I went into our factory in Taichung to figure out like is there anything that that they could do in order to increase the efficiency of a factory and also to do some analysis at that offenders like predicting based on the past two, three years of data.</v>

00:21:58.000 --> 00:21:59.980
<v Patty Shaw>Uh, now we entered.</v>

00:22:00.740 --> 00:22:05.510
<v Patty Shaw>Try to figure out like if we need to umm.</v>

00:22:06.900 --> 00:22:10.050
<v Patty Shaw>Lower our look.</v>

00:22:10.620 --> 00:22:13.760
<v Patty Shaw>The amount of raw material that we order from our vendors.</v>

00:22:14.610 --> 00:22:15.100
<v Patty Shaw>Umm.</v>

00:22:15.550 --> 00:22:15.780
<v Sohail Pathan>OK.</v>

00:22:15.290 --> 00:22:24.630
<v Patty Shaw>So Long story short, we like me and love factory manager and a few of the factory.</v>

00:22:25.650 --> 00:22:26.850
<v Patty Shaw>Uhm, workers.</v>

00:22:29.310 --> 00:22:32.040
<v Patty Shaw>We confirmed their uh.</v>

00:22:34.720 --> 00:22:40.240
<v Patty Shaw>You know, they're understanding that there's a decrease in demand for our product.</v>

00:22:40.890 --> 00:22:53.320
<v Patty Shaw>And So what happens is that we recommended to look Co owners that we should lower the orders cause we already have some inventory of raw material in factory.</v>

00:22:53.410 --> 00:23:10.260
<v Patty Shaw>And so we kind of pause the ordering frequency from our vendors and create a new understanding with them that we're gonna use up where we already have before we place new orders and the new orders wouldn't be periodic anymore.</v>

00:23:15.060 --> 00:23:15.380
<v Sohail Pathan>Right.</v>

00:23:10.300 --> 00:23:43.780
<v Patty Shaw>It wouldn't be like on set because anymore it will be based on whenever we need it like 2 weeks beforehand we'll reach out to them to get the material to start being shipped from China and then from there we also just looking at the data and like ohh different people in the company have already picked it up from you know the decrease in incoming requires to get quotes from the you know inquiry to come to customer conversion rate.</v>

00:23:43.950 --> 00:24:08.580
<v Patty Shaw>And so our data together and with all analysis from different people have confirmed that we are probably going to enter kind of like a business winter for our company and we need to lower what we order from the vendor and we also kind of like decrease the quantity of a product that we produce in the factory.</v>

00:24:10.240 --> 00:24:11.270
<v Sohail Pathan>If you're makes sense.</v>

00:24:11.550 --> 00:24:15.710
<v Sohail Pathan>So we are not on time, but I still need your two minutes.</v>

00:24:15.720 --> 00:24:16.450
<v Sohail Pathan>Would that be OK?</v>

00:24:17.470 --> 00:24:18.690
<v Patty Shaw>Yes, that'll be OK.</v>

00:24:19.760 --> 00:24:20.210
<v Sohail Pathan>All right.</v>

00:24:20.270 --> 00:24:21.640
<v Sohail Pathan>So last one for you.</v>

00:24:22.390 --> 00:24:38.190
<v Sohail Pathan>Uh, consider me as a non technical stakeholder and I want you to demonstrate how well or how effectively you can convey or communicate me complex data insight.</v>

00:24:40.730 --> 00:24:41.010
<v Patty Shaw>OK.</v>

00:24:44.270 --> 00:24:45.910
<v Patty Shaw>Let me think of an example.</v>

00:24:44.940 --> 00:24:53.410
<v Sohail Pathan>You can take any example out of your previous work and thinking of me as a non technical stakeholder.</v>

00:24:54.720 --> 00:24:59.830
<v Patty Shaw>OK, so all the coworkers at my current company.</v>

00:24:59.840 --> 00:25:00.400
<v Patty Shaw>They're non-technical.</v>

00:25:01.270 --> 00:25:05.380
<v Patty Shaw>Umm, one of them is my uncle and then umm the other coworkers are.</v>

00:25:05.570 --> 00:25:13.220
<v Patty Shaw>The other co-owners are all like older than him, so they have never used Excel and their life.</v>

00:25:13.860 --> 00:25:14.110
<v Sohail Pathan>Mm-hmm.</v>

00:25:13.610 --> 00:25:25.920
<v Patty Shaw>People underneath them use excel for them and then tell them the number like previously they don't even prior to Tableau, they don't even look at like data sets or even like the Excel generated graphs.</v>

00:25:26.800 --> 00:25:44.220
<v Patty Shaw>Umm, so one of the challenges was for example like when we first digitize the data by data entry into the system and creating a the database to them, it was hard for them to understand why we needed it.</v>

00:25:44.890 --> 00:25:58.450
<v Patty Shaw>Umm, so we have to like me and my coworker and UM, our manager, like the office manager who came up with the idea of like digitizing all the data.</v>

00:25:59.820 --> 00:26:10.230
<v Patty Shaw>We have to convince them so one of the arguments that I made was, first of all, like everyone will have access to the same information.</v>

00:26:10.640 --> 00:26:13.930
<v Patty Shaw>Like it doesn't matter where they are within the company told him.</v>

00:26:13.940 --> 00:26:31.710
<v Patty Shaw>Poll everyone will be able to have access to the data and could do analysis and and what that means is they could use the data and different people with their different personal different, you know personal preferences or their personal experience.</v>

00:26:31.820 --> 00:26:58.680
<v Patty Shaw>They will see different trends or different insights within those data and because of that they could better tie the insights into their row and based on because it's a small company because we have insights into other peoples role and what they do, we can make recommendations to other people and help make their roles more efficient.</v>

00:26:59.170 --> 00:27:00.170
<v Patty Shaw>And on top of that?</v>

00:27:00.810 --> 00:27:08.410
<v Patty Shaw>Umm, when we come up with different insights and we as a team develop it.</v>

00:27:08.640 --> 00:27:17.110
<v Patty Shaw>Improvement opportunities for each other as a whole accompany becomes more efficient and for example in the.</v>

00:27:19.090 --> 00:27:29.320
<v Patty Shaw>In the recommendation to the Co owners in order to decrease our orders from the vendors that was first identified by a line worker in the factory.</v>

00:27:29.630 --> 00:27:33.630
<v Patty Shaw>And so she recommended it to her manager.</v>

00:27:33.640 --> 00:27:45.050
<v Patty Shaw>And then her manager reached out to my office manager and then together she told me and my coworker, my data analyst coworker to go figure it out.</v>

00:27:52.270 --> 00:27:52.580
<v Sohail Pathan>Right.</v>

00:27:45.340 --> 00:28:25.010
<v Patty Shaw>Based on what data and then after we did some research and kind of confirming the direction, we decided that we need to go and work at the factory for a month and kind of like observe their day to day and at the same time discover places or in the procedure that could be improved and also further confirmed that yeah, we do have more than enough we based on our data from our sales force we could see that we can forecast that umm our customer demand is decreasing too and we did lose some customers over the past.</v>

00:28:25.140 --> 00:28:25.490
<v Patty Shaw>Year.</v>

00:28:25.500 --> 00:28:40.030
<v Patty Shaw>So altogether, that's how we were able to convince our Co owners who are not technical, that using the data is a great way to confirm what people have business sense in.</v>

00:28:42.450 --> 00:28:43.110
<v Sohail Pathan>OK, thing.</v>

00:28:43.800 --> 00:28:44.450
<v Sohail Pathan>All right.</v>

00:28:44.500 --> 00:28:48.750
<v Sohail Pathan>So that's all I had in my mind to discuss with you.</v>

00:28:48.760 --> 00:28:52.370
<v Sohail Pathan>Do you have any last moment questions or anything that you need from me?</v>

00:28:54.620 --> 00:28:57.490
<v Patty Shaw>What is your favorite thing about Quest Global?</v>

00:28:58.440 --> 00:29:06.700
<v Patty Shaw>And then why have you decided to stay with Quest Global instead of like going into one of the clients that you've worked with over the years?</v>

00:29:08.600 --> 00:29:25.220
<v Sohail Pathan>So, uh, my the thing I would say about my favorite thing about Quest Global is the culture over here is very friendly, very good that I like and it makes me feel like home.</v>

00:29:30.710 --> 00:29:31.010
<v Patty Shaw>OK.</v>

00:29:25.280 --> 00:29:31.370
<v Sohail Pathan>So that's the reason I have never thought of walking off to any other client if.</v>

00:29:33.190 --> 00:29:40.030
<v Patty Shaw>And then, umm, a follow up question to our interview, what are the next steps and timelines?</v>

00:29:41.250 --> 00:30:04.560
<v Sohail Pathan>So you next step is by this week aimed our chat team would connect with you based on the decision we make and uh after HR teams connect with you, they would set up a small technical discussion with someone from HP, probably the manager with whom you would be working.</v>

00:30:05.030 --> 00:30:18.170
<v Sohail Pathan>And once that discussion is done, we should expect a decision within two to three days, and once we have that decision, your HPID creation and onboarding will get started.</v>

00:30:20.020 --> 00:30:20.390
<v Patty Shaw>OK. Yeah.</v>

00:30:22.360 --> 00:30:26.470
<v Patty Shaw>And then how many people are you guys currently interviewing for this position?</v>

00:30:28.140 --> 00:30:33.150
<v Sohail Pathan>So right now I don't have that data because there are multiple folks.</v>

00:30:33.160 --> 00:30:40.150
<v Sohail Pathan>Those how those are interviewing for this position and I was just brought into this last week.</v>

00:30:40.210 --> 00:30:41.930
<v Sohail Pathan>So I'm not really sure about that.</v>

00:30:43.310 --> 00:30:44.300
<v Patty Shaw>OK, no worries.</v>

00:30:44.310 --> 00:30:45.760
<v Patty Shaw>I could always follow up with Allwin.</v>

00:30:46.600 --> 00:30:46.840
<v Sohail Pathan>Sure.</v>

00:30:46.500 --> 00:30:47.150
<v Patty Shaw>Yeah.</v>

00:30:47.280 --> 00:30:47.610
<v Patty Shaw>Thank you.</v>

00:30:47.780 --> 00:30:49.040
<v Patty Shaw>Thank you so much for your time.</v>

00:30:50.040 --> 00:30:50.850
<v Sohail Pathan>Thank you so much.</v>

00:30:50.860 --> 00:30:51.920
<v Sohail Pathan>Have a nice day ahead.</v>

00:30:51.930 --> 00:30:52.120
<v Sohail Pathan>Bye. Bye.</v>

00:30:52.630 --> 00:30:53.490
<v Patty Shaw>You too. Bye.</v>
" 

Based on this interview transcript how suitable is Patty Shaw for this role?