Aakanksha Jha
Data & Applied Scientist at Microsoft
Data & Applied Scientist  at Microsoft
★ Experienced Data & Applied Scientist  of 8 years experience with a passion to develop Statistical/Machine Learning/Deep Learning models which contributes to the growth of the product.
★ Skilled in Machine Learning, Data Mining, Data Optimization and Decision Modelling, Data visualisation, Statistical Inference, Regression Modelling and Techinques.
Knowledge of Recommendation Engine,Text Mining, Social Network Analysis
★ Programming skills:  R, Python, SAS
★Database Management System:  SQL 
★Data Visualisation: PowerBI, Tableau
Microsoft
https://www.linkedin.com/company/microsoft
Data & Applied Scientist
Microsoft Azure
Microsoft 365 Team
Microsoft Compete
Microsoft Security and Identity
Greater Seattle Area
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APL Logistics
https://www.linkedin.com/company/apl-logistics
Capstone Project
1.Developed an Advance Analytics Framework for Supply Chain .
2.Monetization of 3PL data.
3.Create a use case for analytics framework.
United States
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Accenture
https://www.linkedin.com/company/accenture
Software Engineer
Mumbai Area, India
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Accenture
https://www.linkedin.com/company/accenture
Associate Software Engineer
Mumbai Area, India
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Business Analytics
Master of Science - MS
Arizona State University - W. P. Carey School of Business
https://www.linkedin.com/school/wpcareyschool/
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BE in Computer Science
Bachelor of Engineering (BEng)
University of Mumbai
https://www.linkedin.com/school/university-of-mumbai/
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Associate of Science - AS
R. D. National College
https://www.linkedin.com/school/r.-d.-national-college/
Post  Secondary  Education
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Engage Charitable Trust-Non Profitable Organization
Feedback Analyst
W. P. Carey GPO Merit Scholarship.
Arizona State University
Received a scholarship for pursuing Masters in Business Analytics at the W.P.Carey School of Business.
Outperformer Award at Accenture
Accenture Solutions Pvt Ltd
Applied Analytics
SCM516
Business Analytics Case Study
CIS593
Data Driven Quality Management
SCM517
Enterprise Analytics
CIS505
Marketing Analytics
MKT591
Advance Decison Modelling
SCM518
Data Mining 1
CIS508
Data Mining 2
CIS509
Decision Modelling
SCM518
Job Search Strategies
CIS594
APL Logistics
Working for Advance Analytics Framework in the era of supply chain disruptions.
Monetization of 3PL Data
House Prices: Advanced Regression Techniques
*Worked on Preprocessing of data which is merging of files and data cleaning in R script by using
  MICE() function which clean missing value .
*Worked on feature Engineering in R and got the derived features using Sparse matrix adding value to 
  the data and increasing the accuracy.
*Ran the model using boosted decision tree regression, linear regression and neural network
  regression with different features and hyperparameter tuning.
 *Worked on Stacked ensembling with cross validation tuning and got the best Kaggle score of 0.16.
https://www.kaggle.com/c/house-prices-advanced-regression-techniques
Profit Optimization At KOLBY’S (Data Modelling)
*Analyzed the daily operation data of Kolby’s and generated an operating reference with   optimized day wise floating price .
* Used Constant Elasticity of Demand on the data and created a model to maximize profit by  calculating the floating price per day per slot.
*Basded on the optimization the owner could make 70% profit from the past records.
https://www.kolbys.net/
Design of experiments to build a  race car using Lego sets(Minitab)
*Designed a car model using lego blocks with a goal to maximize the distance and optimized cost using Minitab.
*Used 4 factors, using 2 raised to k =16 observation, 3 replicates and a total of  48 observations and performed the experiment with 48 trails with different factors on every run.
* Recorded observations on Minitab andperformed the model adequacy check and recorded the most contributing significant factors from the pareto ,normal probability plot ,Residual Analysis and came to the best contributing factors for the car covering the maximum distance.
Kaggle Project:Predict service faults on Telstra Network Disruptions(Machine Learning)
*Worked on Preprocessing of data which is merging of files and data cleaning in R script by using dcast()
* Worked on feature Engineering in R and got the derived features usingSparse matrix 
*Ran the model with and without Cross Validation with different multiclass algorithms using
hyperparameter tuning. 
*Worked on Stacked ensembling with cross validation tuning .
https://www.kaggle.com/c/telstra-recruiting-network
Perform Clustering for Time Series Dataset
*Performed clustering using K-Means and Kohonen methods on the dataset.
*Verified whether there lies a similarity in the pattern of lustering for the Kmeans and Kohonen.
https://archive.ics.uci.edu/ml/datasets/Sales_Transactions_Dataset_Weekly
Porto Seguro’s Safe Driver Prediction
*Performed EDA ,Data Cleaning using SMOTE Analysis ,Treatment of Missing values.
*Performed Feature Based Selection using Pearson Corelation 
*Performed classification using Two Class Neural Networ,Two Class Support Vector Machine,Two Class Boosted Decision Trees,Two Class Decision Jungle,Two Class Decision Forest.
*Performed stacked ensembling
https://www.kaggle.com/c/porto-seguro-safe-driver-prediction
Fraud Detection for bank
*Performed Exploratory data Analysis and conducted SMOTE means of sampling for the data set for imbalanced dataset.
*Used hyperparameter tuning and used classification method using two class decision forest,two class decision jungle and two class decision forest  for the best model predicting accurate results.
Target Marketing-Portugese Bank Data
*Performed initial Exploratory Data Analysis on the train data set .
*Analysed the data imbalance in the dataset.
*Performed hyperparameter tuning FScore and Accuracy as the main performance criteria .
*Used classification algoriths like Two class Boosted Decision Forest,Two Class Decision Jungle and Two Class Decision Forest for Best performing algorithm and best results.
http://archive.ics.uci.edu/ml/datasets/Bank+Marketing
Tableau Visual analytics Project- Sean Lahman’s baseball dataset(Tableau)
*This database was created by Sean Lahman, on Major League Baseball (MLB) 
* Performed various calculations for the the trend of players in baseball having maximum or minimum salary,average performance,winning and losing teams ,etc by using Tableau.
* Combined  datasets through joins and merged in one data and based on requirement created graphs,heat map to visualise various components of the baseball league using Tableau.
Fortune Mining500 Company(SAP)
Predict if  a  Customer would default performing credit  bucketting for customers.
Performed Market Basket Analysis using Association rule
http://www.bhpbilliton.com
Fortune Mining500 Company
Developed and Customised configurations in Financial Accounting and Ticketing Relevancy setup Training provided to the end user as well as the fellow team members in logistics execution and sales and
distribution.
http://www.south32.net
Gesture Recognition (MATLAB)
The objective of doing a project on Gesture Recognition was Controlling Computer Using Hand Gesture
Recognition”. 
This was our Final Year BE project and we also presented a short length Technical Paper in the International Conference and Workshop on Electronics and Telecommunication Engineering at TCET and receivedappreciation for the design and documentation
https://coursera.org/share/be3c8b509118c8e5108750229d1f5248
Python Data Structures
37E4VS6N7TLU
coursera.org
Coursera
https://coursera.org/share/8c04bb34032be3cd917b59941b403730
Python for Everybody Specialization
5MU3FB65P5W2
coursera.org
Coursera
https://www.datacamp.com/statement-of-accomplishment/course/d0ee257a2c83e62ed969f892b6ef71fc36acd103
Cleaning Data in Python Course
d0ee257a2c83e62ed969f892b6ef71fc36acd103
www.datacamp.com
DataCamp
https://www.datacamp.com/statement-of-accomplishment/course/6550bc966da5b332022a4ceb4fa8101408ba4a40
Intermediate Python for Data Science Course
6550bc966da5b332022a4ceb4fa8101408ba4a40
www.datacamp.com
DataCamp
https://www.datacamp.com/statement-of-accomplishment/course/b0f3f88f12f86198514826a9f5dd88ac9e1d4f6c
Intro to Python for Data Science
b0f3f88f12f86198514826a9f5dd88ac9e1d4f6c
www.datacamp.com
DataCamp
https://www.coursera.org/account/accomplishments/certificate/8KLGQM334DAJ
Practical Machine Learning
8KLGQM334DAJ
www.coursera.org
Coursera
https://www.datacamp.com/statement-of-accomplishment/course/4677bd31be261bee29b95d19402301e84e3e0ebd
Python Data Science Toolbox (Part 1) Course
4677bd31be261bee29b95d19402301e84e3e0ebd
www.datacamp.com
DataCamp
https://www.coursera.org/account/accomplishments/verify/UL8VW8TWCVH9
R Programming
UL8VW8TWCVH9
www.coursera.org
Coursera
https://www.coursera.org/account/accomplishments/certificate/2QXB29NAVXM2
Statistical Inference
2QXB29NAVXM2
www.coursera.org
Coursera
https://www.coursera.org/account/accomplishments/verify/7CGKBX7QXSAZ
The Data Scientist’s Toolbox
7CGKBX7QXSAZ
www.coursera.org
Coursera
https://eprofessional.bcs.org/Portal/eCertCheck
Foundation Certificate in Business Analysis (2015)
271280
eprofessional.bcs.org
BCS, The Chartered Institute for IT
ITIL R Foundation Examination
ITIL/MY794744
AXELOS Global Best Practice
Accenture  GFT
Accenture
INFOSYS FOUNDATION TRAINING
Infosys
https://analytics.google.com/analytics/academy/course/7/certificate
Advanced Google Analytics
analytics.google.com
Google, Social Marketing Tools
https://analytics.google.com/analytics/academy/course/3/certificate
Ecommerce Analytics: From Data to Decisions
analytics.google.com
Google, Social Marketing Tools
https://analytics.google.com/analytics/academy/course/6/certificate
Google Analytics for Beginners
analytics.google.com
Google, Social Marketing Tools
http://coursera.org/verify/5Y7NE8B6W8K6
Social Network Analysis
5Y7NE8B6W8K6
coursera.org
Coursera
The Data Science of Experimental Design
ActDxTqe4GV4v_ewzJr7OcRS1L-P
LinkedIn
Test your HiPPOpinions poster mockup that showed up on my "On this day 14 years ago."  The ExP team tried to change the culture at Microsoft to run…
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If you are shipping features without running a *controlled* experiment, you are really running an *inefficient* experiment, where analysis is done by…
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Aakanksha Jha
https://ca.linkedin.com/in/aakankshajha91
Manager | Project Delivery & Management at RBC
Toronto, ON
Aakanksha Jha
https://in.linkedin.com/in/aakanksha-jha-086589213
Sophomore@IGDTUW'24 || General secretary at Cognito SDG
New Delhi
Aakanksha Jha
https://in.linkedin.com/in/aakanksha-jha
Freelance Copywriter, UX Writer, Blog Writer
South Delhi
Aakanksha Jha
https://in.linkedin.com/in/aakanksha-jha-creative-producer
Creative Lead at SUGAR Cosmetics
Mumbai
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ASU's W. P. Carey School of Business Alumni
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Machine Learning and Data Science
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ASU MSBA Class of 2018
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Data Scientist & Analyst
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