We are seeking a mathematically rigorous Data Scientist with a relevant experience of 5-10 years to join our AI and Data team who shall drive business decisions by building robust statistical models, convert the business problem into a statistical problem statement, and developing machine learning algorithms. The ideal candidate pairs a deep foundational understanding of probability and statistics with the technical ability to write clean code and
Key Responsibilities
- Statistical Modelling Analysis: Design, develop, and evaluate advanced statistical and econometric models (e.g., linear/logistic regression, time-series forecasting, Bayesian analysis, and multivariate analysis)
- Machine Learning: Architect, train, and deploy machine learning algorithms (Random Forests, Gradient Boosting, Deep Learning) using frameworks like scikit-learn or TensorFlow
- Experimentation: Design rigorous A/B testing frameworks, formulate hypotheses, and perform power analyses to drive product and marketing decisions.
- Data Pipelines: Write efficient SQL queries to extract, clean,
and manipulate complex data sets for analysis
- Leading the team and Nurture Juniors: Lead the team of junior data scientists and help them in developing data Science and ML models and lead the innvovation amongst team
Required Qualifications
- Education: Degree in Statistics, Mathematics, Operations Research, or a related quantitative field.
- Math Statistics: Deep theoretical and practical knowledge of statistical inference, probability distributions, hypothesis testing, and statistical significance.
- Programming: Robust programming proficiency in Python and PySpark. Advanced proficiency in writing complex SQL
- Communication: Exceptional verbal and written communication skills to articulate complex mathematical models
Preferred Qualifications
- Experience with cloud platform Azure for model deployment.
- Familiarity with big data technologies like Apache Spark or Hadoop