Roles & Responsibilities

• Contribute and build an internal product library that is focused on solving business problems related to prediction & recommendation.
• Participate in building automations and standalone applications around machine learning algorithms to enable a “One Click” solution to getting predictions and recommendations.
• Analyze large datasets, perform data wrangling operations, apply statistical treatments to filter and fine tune input data, engineer new features and eventually aid the process of building machine learning models.
• Apply object-oriented programing and apply design patterns as required, and, participate in designing new features and enhancements to the ML product.
• Work closely with data scientist and help the team with model refresh process and periodic scoring, fixing bugs, re-deploying models in various environments involved in product life cycle.
• Expand and maintain a product based in python and hosted in cloud platforms. Maintain versioning of the library and ensure the new features are integrated into the existing product without affecting the current versions.
• Run test cases to tune existing models for performance, check criteria and define thresholds for success by scaling the input data to multifold.
• Collaborate with client teams to on-board data, build models and score predictions.

Qualifications

Minimum Qualifications:

• Bachelor’s degree in an engineering discipline, but preferably computer science or significant relevant coursework
• Experience building applications from ground up and exposure to object-oriented programing and design patterns will be highly preferred.
• Proficiency with a python advanced concepts such as multi-threading and templating
• Highly skilled in SQL and strong data extraction skills
• Hands-on experience working with very large datasets, including statistical analyses, data visualization, data mining, and data cleansing/transformation
• Demonstrated proficiency in PYTHON and BIG DATA technologies and the proven ability to program in big data/cloud technologies such as AWS & SPARK; minimum 1 years of experience

Desirable Qualifications:

• Basic understanding of machine learning algorithms (Decision Trees, Random Forrest & Regression etc.) and statistical concepts (T-TEST, CHISQ Test, Confidence Interval, Standard deviation, p-value etc.)
• Knowledge and understanding of AWS Sagemaker
• Working experience in CI/CD tools such as GIT & BitBucket