Data Analyst

Inizio is a strategic partner for health and life science businesses. Inizio unlocks the value of healthcare innovation by connecting best-in-class strategic, analytic, and creative capabilities. We bridge scientific knowledge, market intelligence, actionable data, cutting-edge tech, and creative execution- to provide the tailored skills and support that our clients need. We’re a truly global partner with more than 12,500 experts operating in over 50 countries covering all major health and life sciences markets.

Profile

• Previous experience in building data science-based products is big advantage.
• Experience in handling healthcare data (Claims, Trials, RWE) is good to have.

Educational Qualification

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

Typical Experience

• year of 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 statistical programming language
• Mid-level proficiency in MS Excel.

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, Sage maker, machine learning libraries etc. is an added advantage.
• Exposure to big data processing technologies like Spark SQL, PySpark is added advantage.
• Exposure to visualization tools like Tableau is an added advantage.
• Exposure to generative AI tool like ChatGPT, Bard and Llama and prompt engineering is an added advantage.

Primary Responsibility

• Should have experience in EDA, Hypothesis testing, Feature creation, Dimension reduction, Data set clean-up,
• Training models, Model selection, Validation and Deployment)
• Is expected to participate in the discussions during the solution design phase.
• Should have understanding of statistical & machine learning methods ((logistic regression, SVM, decision tree, random forest, Regression (linear regression Logistic)).
• Must have thorough mathematical knowledge of correlation/causation, classification, recommenders, probability and how to implement them to a business problem.
• Expected to gain business understanding in health care domain.
• Familiarity with NLP, Sentiment analysis, text mining , text classification, data scraping solutions.