Data Scientist

What you will be expected to do

• 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

• 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).
  

• 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).
  

• 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.

About
Sun King is the world’s leading off-grid solar energy company, combining cutting-edge product design, fintech, and field operations to deliver energy access for the 1.8 billion people who live without an affordable and reliable electric-grid connection.Sun King has built a new kind of energy utility: distributed, green, customer-centric, and affordable. We bring clean, reliable, decentralized energy directly into people’s lives — from solar kits that provide first-time energy access to multi-kilowatt systems that serve both off-grid users and grid-connected customers powering larger homes, schools, hospitals, farms, offices, and light manufacturing.Already, 25 million homes and businesses rely on Sun King for electricity supply and the appliances and services it enables: lighting, televisions, fans, refrigeration, and smartphones. Sun King combines energy generation, energy-efficient appliances, installation, and financing into one seamless offering. Think of it as a distributed utility, designed for wherever energy is needed and designed to scale with its users as incomes and energy needs grow.Sun King makes solar products affordable to low-income households and businesses via ‘pay-as-you-go’ (PAYG) purchase financing. Sun King installs solar after customers pay a small deposit. Customers then make small, manageable payments of as little as US $0.14 a day via mobile money or cash.Instead of paying for expensive, polluting, and health-damaging kerosene for lighting or diesel for power, customers unlock savings through accessing solar power and after one to two years of payments, customers own their solar equipment outright.Sun King collects payments digitally through mobile money systems and its 35,000 field agents — over 1 million payments each day. To date, Sun King has extended more than $1.4 billion in PAYG loans to customers.Sun King began by powering homes and businesses with solar systems delivered through PAYG financing. Now, we’re using the same model to make smartphones and clean cooking equipment affordable: helping households connect to the digital economy and transition from wood-based fuels to modern, sustainable alternatives.Sun King employs 3,500 full-time staff in 14 countries, with specialties spanning product design, data science, logistics, customer service, sales, software, operations, and more — all with a passion to serve off-grid families. Sun King is committed to gender diversity in the workplace. Women represent 42% of Sun King’s workforce.