About the role

Design, build, and evaluate classical machine learning models to translate complex datasets into actionable business insights. Collaborate with engineering teams to maintain data pipelines and communicate model performance to stakeholders.

What they look for

Machine learning Python SQL Bayesian modeling Probabilistic modeling Data science Feature engineering Data wrangling Statistical analysis PyMC Scikit-learn XGBoost Model evaluation A/B testing Cloud data warehouses MLflow

Requirements

Requires 3-4 years of hands-on experience in data science with strong proficiency in Python, SQL, and Bayesian modeling. Candidates must hold a degree in a quantitative discipline such as Computer Science, Statistics, or Mathematics.

Benefits

Professional growth Collaborative culture Multicultural experience Structured learning and development programs

Full description

Data Scientist

Department: Global Analytics and Technology

Employment Type: Permanent - Full Time

Location: India

Description

Job location: Remote

About the role:

We are looking for a skilled Data Scientist who can translate complex datasets into actionable business insights through rigorous statistical analysis and machine learning. The ideal candidate combines strong foundational knowledge of classical ML with a solid grasp of probabilistic and Bayesian modeling, and can operate effectively across the full spectrum from data exploration to production-ready model delivery.

What you will be expected to do

KEY RESPONSIBILITIES

Design, build, and evaluate classical machine learning models for business-critical use cases (classification, regression, ranking, anomaly detection, time-series forecasting).

Apply probabilistic and Bayesian modeling techniques to quantify uncertainty and inform decision-making under uncertainty; leverage tools like PyMC and PyMC-Marketing for Bayesian workflows.

Perform rigorous EDA, feature engineering, and data wrangling on large structured and semi-structured datasets using Python and SQL.

Collaborate with data engineers and analytics engineers to source, clean, and validate data pipelines feeding ML workflows.

Develop, track, and communicate model performance metrics; identify degradation signals and recommend retraining or improvement strategies.

Translate business questions into well-framed statistical problems and present findings clearly to technical and non-technical stakeholders.

Maintain clean, reproducible, and well-documented code and notebooks following team engineering standards.

You might be a strong candidate if you have/are

REQUIRED SKILLS & QUALIFICATIONS

3–4 years of hands-on experience in a data science or applied ML role.

Strong command of classical ML algorithms - gradient boosting, random forests, SVMs, logistic regression, clustering, dimensionality reduction, etc.

• scikit-learn, XGBoost, LightGBM, CatBoost.Proficiency with ML frameworks:

• PyMC or PyMC-Marketing.Solid understanding of probabilistic modeling, Bayesian inference, and uncertainty quantification; working experience with

• Python (pandas, NumPy, SciPy, matplotlib/seaborn/plotly, MLflow).High proficiency in

• SQL skills - complex multi-table queries, window functions, performance optimization.Strong

Deep familiarity with model evaluation frameworks: cross-validation, calibration, AUC, RMSE, MAPE, lift/gain curves, and business-aligned metrics.

Experience with experiment design, A/B testing, and statistical hypothesis testing.

Comfortable working 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 libraries (Prophet, statsmodels, sktime).

Prior work in fintech, PAYG, or emerging markets contexts.

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

EDUCATION

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

What Sun King offers

Professional growth in a dynamic, rapidly expanding, high-social-impact industry

An open-minded, collaborative culture made up of enthusiastic colleagues who are driven by the challenge of innovation towards profound impact on people and the planet.

A truly multicultural experience: you will have the chance to work with and learn from people from different geographies, nationalities, and backgrounds.

Structured, tailored learning and development programs that help you become a better leader, manager, and professional through the Sun King Center for Leadership.