The Data Scientist is a key role in the Analytics team which brings together data scientists, actuaries and business analysts to partner with colleagues across Underwriting, Product, Finance, and Technology to develop advanced analytics and machine learning solutions that strengthen underwriting models, risk selection, pricing, and pricing strategy across Insurance.

Skills and expertise required:

- Advanced degree (Masters, Ph.D.) in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial, Data Science, or comparable quantitative disciplines.

Applied experience with several of the following:

- Data Acquisition and Transformation: Acquiring data from disparate data sources using APIs, SQL and NoSQL. Transform data using SQL, NoSQL, and Python. Visualizing data using a diverse tool set including but not limited to Python and R.
- Model Deployment: Understanding of: MDLC (Model Development Life Cycle), CI/CD/CT pipelines (using tools like Jenkins, CloudBees, Harness etc.), A/B testing.




- Statistics and Computing: Exceptional understanding of: Calculus, Multivariable Calculus, Linear Algebra, Differential Equations, Probability, Statistics, Applied Probability, Applied Statistics, Computer Science (Programming Methodologies), and Cloud. Knowledge of statistical techniques such as the use of descriptive, inferential, Bayesian statistics, time series analysis etc. to extract business insights and experimentation to solve business problems
- Machine Learning: Understanding of machine learning theory, including the mathematics underlying machine learning algorithms. Expertise in the application of machine learning theory to building, training, testing, and monitoring machine learning models. Understanding and expertise in NLP (natural language processing).
- Programming Languages: Python, R, SQL,

📌 Data Scientist - 7 To 10 Years - Gurgaon (Gurugram)
🏢 Crescendo Global Leadership Hiring India
📍 Gurugram