Data Scientist

This is a fully remote position, open to applicants in India.

📋 Description

• Design, develop, and assess traditional machine learning models for essential business applications (classification, regression, ranking, anomaly detection, time-series forecasting).

• Utilize probabilistic and Bayesian modeling methodologies to measure uncertainty and guide decision-making processes in uncertain environments; employ tools such as PyMC and PyMC-Marketing for Bayesian workflows.

• Conduct thorough exploratory data analysis (EDA), feature engineering, and data manipulation on extensive structured and semi-structured datasets using Python and SQL.

• Work in conjunction with data engineers and analytics engineers to acquire, cleanse, and verify data pipelines that support ML workflows.

• Create, monitor, and relay model performance metrics; detect signs of performance decline and suggest retraining or enhancement strategies.

• Convert business inquiries into well-defined statistical challenges and present results effectively to both technical and non-technical audiences.

• Ensure the maintenance of clean, reproducible, and well-documented code and notebooks in accordance with team engineering best practices.

⛳️ Requirements

• 3–4 years of practical experience in a data science or applied machine learning position.

• Strong understanding of classical ML algorithms including gradient boosting, random forests, SVMs, logistic regression, clustering, and dimensionality reduction.

• Proficiency in ML frameworks such as scikit-learn, XGBoost, LightGBM, and CatBoost.

• Experience with PyMC or PyMC-Marketing, along with a solid grasp of probabilistic modeling, Bayesian inference, and uncertainty quantification.

• Proficient in Python (pandas, NumPy, SciPy, matplotlib/seaborn/plotly, MLflow) and possess strong SQL skills for complex multi-table queries, window functions, and performance optimization.

• Deep familiarity with model evaluation techniques, including cross-validation, calibration, AUC, RMSE, MAPE, lift/gain curves, and business-related metrics.

• Experience in designing experiments, A/B testing, and conducting statistical hypothesis testing.

• Comfortable with cloud data warehouses (AWS Redshift, BigQuery, Snowflake) and standard ML experiment tracking tools (MLflow, W&B).

• NICE TO HAVE: Exposure to survival modeling, causal inference, or marketing mix modeling (MMM).

• Experience with time-series forecasting frameworks (Prophet, statsmodels, sktime).

• Previous experience in fintech, PAYG, or contexts related to emerging markets.

• Familiarity with MLOps pipelines and model deployment on AWS (SageMaker, Lambda, ECS).

• B.Tech / B.E. / B.Sc. / M.Tech / M.Sc. in Computer Science, Statistics, Mathematics, Engineering, or a closely related quantitative field.

🏝️ Benefits

• Professional advancement in a vibrant, rapidly growing, high-social-impact sector.

• A collaborative and open-minded culture comprised of passionate colleagues motivated by the challenge of innovation aimed at making a significant impact on individuals and the planet.

• A genuinely multicultural environment: you will have the opportunity to work alongside and learn from individuals from diverse geographies, nationalities, and backgrounds.

• Structured, personalized learning and development initiatives designed to enhance your abilities as a leader, manager, and professional through the Sun King Center for Leadership.