Senior Analyst, Research Analytics

Profile

·       Previous experience in building data science based products is big advantage.

·       Experience in handling healthcare data is desired.

Educational Qualification

•        Bachelors / Masters in computer science or related subjects from reputable institution

Typical

Experience

•        3-5 years experience of industry experience in developing data science models and solutions.

•        Able to quickly pick up new programming languages, technologies, and frameworks

•        Strong understanding of data structures and algorithms

•        Ability to work in a start-up environment with a do it yourself attitude.

Skill and Expertise

•        Expert level proficiency in programming language Python/SQL.

•        Working knowledge of Relational SQL and NoSQL databases, including Postgres, Redshift

•        Exposure to open source tools & working on cloud platforms like AWS and Azure and being able to use their tools like Athena, Sagemaker, machine learning libraries is an added advantage

•        Exposure to big data processing technologies like Pyspark, SparkSQL added advantage

•        Exposure to AI tools LLM models Llama (ChatGPT, Bard) and prompt engineering is added advantage

•        Exposure to visualization tools like Tableau, PowerBI is an added advantage

Primary

Responsibility 

·       As a senior analyst the individual will be providing technical expertise to the team

·       Should be expert in all phases of model development (EDA, Hypothesis, Feature creation, Dimension reduction, Data set clean-up, Training models, Model selection, Validation and Deployment)

·       Is expected to participate and lead discussions during the solution design phase.

·       Should have deep understanding of statistical & machine learning methods ((logistic regression, SVM, decision tree, random forest, neural network), Regression (linear regression, decision tree, random forest, neural network), Classical optimisation (gradient descent etc),

·       Must have thorough mathematical knowledge of correlation/causation, classification, recommenders, probability, stochastic processes, NLP, and how to implement them to a business problem.

·       Expected to gain business understanding in health care domain  order to come up with relevant analytics use cases. (E.g. HEOR / RWE / Survival modelling)

·       Familiarity with NLP, Sentiment analysis, text mining , data scraping solutions.