Position: Machine Learning Engineer (1555)
Company: Exadel
Category: Data Science
Experience required: 5y
English level: intermediate
Published: 2021-10-01T00:00:00+03:00

Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and programming. If you also have knowledge of data science and software engineering, we’d like to meet you.

**Work at Exadel - Who We Are:**
Since 1998, Exadel has been engineering its own software products and custom software for clients of all sizes. Headquartered in Walnut Creek, California, Exadel currently has 1400+ employees in development centers across America, Europe, and Asia. Our people drive Exadel’s success, and they are at the core of our values, so Exadel is a people-first cultured company.

**About Our Customer:**
The customer is a leader in actionable analytics or sales effectiveness. It is revolutionizing how field sales teams make their day-to-day decisions, providing them with real-time, in-context, and in-workflow smart suggestions that have been shown to meaningfully improve rep performance. Smart suggestions, driven by data, help reps better navigate sales decisions such as which prospects to call, when and where to call on them, what products to position, which messages to use, and why.

**About Our Project:**
The Customer provides a salesforce data based intelligence platform, that analyzes all daily activity of pharmaceutical company representatives around all regions, providing intelligent suggestions of actions to boost engagements and sales. Historically, 100% of suggestions were done using statically coded business rules, defined per customer. Now, the system is getting ML-driven enhancements on top of those static rules. For example, the business rules engine decides that it is time to send an email to a health care provider (HCP), but ML models decide which template is more likely to appeal to a given HCP and on which days they most often open promotional materials as opposed to the days they never read them. The same can be done in regards to personal visits, medical conferences invites, etc.

ML modules in the Customer’s company are undergoing real case-studies after deployment to prove the concept. And the results are driving real-world engagement increase. For reference - "just" 4% engagement increase (from one of the studies) is a huge win in a multi-billion and highly competitive industry.

Our ideal candidate will have extensive knowledge of Big Data and ML; specifically, how to organize and architect ML modules. Our ML-specialized team only works on ML projects and has active and case-studies proven ML modules in production (and is working on new ones all the time). We're looking for a talented professional to bring strong architectural advice to the table.

**Project Team:**
This is a dedicated scrum team with about 5 engineers (several ML-related PhDs among them), 2 QAs, and a scrum master.

**Requirements:**
- 5+ years of relevant experience with a proven track record of developing algorithms and machine learning products for production ready recommendation or prediction systems using languages and big data platforms such as Scala, Python, R, Java, Spark, Cassandra, and Hadoop.
- Deep understanding and experience in Big Data concepts
- Extensive knowledge of ML frameworks, libraries (e.g. Scikit, Numpy, Pandas, TensorFlow, R ML packages), tools (AWS EMR, Databricks, Knime, etc), data structures, data modeling concepts
- Able to organize and architect ML modules 
- In-depth knowledge of mathematics, statistics, and algorithms (Random Forests, General Linear Regression, Elastic Nets, Clustering, and NLP)
- Superb analytical and problem-solving abilities
- Great communication, collaboration skills, time management and organizational abilities
- BS/MS in Computer Science, ML, Mathematics, or related field and/or equivalent work experience

**Nice to have:**
- 1+ projects playing the lead role in architecting/designing middle-tier, ML or database layers for a new application.
- Design/use schemas in various data storage platforms (MySQL, DataLake, S3, Snowflake)
- Experience in design/development of RESTful APIs in Java(Spring)
- Experience in front-end development (React/Redux)

**Responsibilities:**
- Analyze and improve existing data science modules
- Design new machine learning modules according to requirements
- Research and advise on appropriate ML algorithms, tools and integration/deployment strategies
- Select appropriate datasets and data representation methods
- Run machine learning tests and experiments
- Use test results to perform statistical analysis and fine-tuning
- Train and retrain systems when necessary
- Extend existing ML libraries and frameworks
- Keep abreast of developments in the field

**Advantages of Working with Exadel:**
- You can build your expertise with our Sales Support team, who provide assistance with existing and potential projects
- You can join any Exadel Community or create your own to communicate with like-minded colleagues
- You can participate in continuing education as a mentor or speaker 
- You can take part in internal and external meetups as a speaker or listener. We support you in broadening your horizons and encourage knowledge sharing for all of our employees
- You can learn English with the support of native speakers
- You can take part in cultural, sporting, charity, and entertainment events
- Working at Exadel means always upgrading your skills and proficiency, so we provide plenty of opportunities for professional development. If you’re looking for a challenge that will lead you to the next level of your career, you’ve found the right place 
- We work hard to ensure honest and open relations between employees and leadership, so our offices are friendly environment