Powering access to brighter lives in Africa, Asia, and beyond.
Data Scientist
Location
India
Posted
7 days ago
Salary
0
Seniority
Senior
Job Description
Data Scientist
Sun King
• 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.
Job Requirements
- 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).
- B.Tech / B.E. / B.Sc. / M.Tech / M.Sc. in Computer Science, Statistics, Mathematics, Engineering, or a closely related quantitative discipline.
Benefits
- 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.
Related Guides
Related Categories
Related Job Pages
More Data Scientist Jobs
• Innovate and improve machine learning models for financial progress • Collaborate on designing, developing, and deploying machine learning models • Partner with business leaders and technical experts to develop new data sources • Apply models with sound risk management
Senior Pricing Data Scientist
FivetranFivetran is the leader in automated data integration, delivering ready-to-use connectors that adapt to change.
• Analyze product usage, deal, financial, and billing data to model pricing, packaging, and monetization scenarios. • Design frameworks to assess willingness to pay, customer value, and price realization across customer segments and product lines. • Conduct research on pricing strategies, packaging models, and monetization approaches across comparable and adjacent markets. • Lead pricing and packaging strategy for new product launches, partnering with Product, GTM, and Finance to define commercial models • Build value-based pricing and econometric models to quantify elasticity, customer ROI, and lifetime value. • Design and execute pricing experiments • Synthesize quantitative analysis, customer research, and competitive intelligence into executive recommendations that influence pricing strategy. • Drive customer and prospect research to understand purchasing behavior, value perception, and pricing friction. • Partner closely with Product, Analytics, Finance, Sales, Marketing, and Legal to deliver end-to-end pricing initiatives. • Define KPIs and dashboards that measure pricing performance and identify optimization opportunities. • Continuously evolve our pricing and packaging strategy to improve ARR growth, customer adoption, and value realization.
Role Description Estamos em busca de um(a) Cientista de Dados para atuar no desenvolvimento de soluções analíticas avançadas, modelos preditivos e algoritmos de otimização que apoiem a tomada de decisão estratégica do negócio. O profissional será responsável por transformar problemas complexos em soluções matemáticas e computacionais escaláveis, utilizando técnicas de Machine Learning, Pesquisa Operacional e Otimização Matemática. Qualifications - Experiência sólida como Cientista de Dados atuando em projetos de Machine Learning. - Conhecimento avançado em algoritmos clássicos de Machine Learning (Regressão Linear e Logísta, Árvores de Decisão, Séries Temporais, etc). - Experiência em modelagem estatística e análise de dados. - Conhecimento em Otimização Matemática e Pesquisa Operacional. - Proficiência em Python e bibliotecas de Data Science (Pandas, NumPy, Scikit-Learn). - Experiência com SQL para manipulação e análise de dados. - Conhecimento de versionamento de código utilizando Git. - Pensamento analítico e visão sistêmica. - Capacidade de resolver problemas complexos de negócio. - Comunicação clara com públicos técnicos e executivos. - Proatividade e autonomia. - Colaboração e trabalho em equipe. - Orientação para resultados e geração de valor para o negócio. Requirements - Experiência em ambientes de nuvem (Azure, AWS ou GCP). - Conhecimento em MLOps e monitoramento de modelos. - Experiência com Databricks, Microsoft Fabric ou plataformas de Analytics em larga escala. Benefits - Política de Home Office. - Plano de saúde, com cobertura nacional. - Plano odontológico. - Convênio com Sesc. - Wellhub. - Vale refeição ou alimentação. - Auxílio creche. - Participação nos resultados. - Licença parental estendida. - Plano de desenvolvimento individual/anual com subsídio para capacitação. - Treinamento do idioma inglês.
• Lead studies including (but not limited to) a combination of healthy volunteer and patient populations, multi-site, complex protocol design, strong client management required or reduced timelines. • Ability to organize and effectively prioritize workload and deliverables. • As the Study Manager, be accountable for all DM deliverables as assigned per the established timeline; providing instruction to their DM study team(s) and review of their study team’s output to ensure the highest quality, while adjusting resource allocations accordingly. • Ensure that all allocated projects are carried out in strict accordance with the relevant protocols, global harmonized SOPs, and the specified standards of GCPs. • Work with the Project Manager(s) or FSP Lead (or designee) to build timelines to meet contracted milestones by communicating with leads in different disciplines and the full project team as necessary, including at study initiation meetings. • Provide DM project team leadership and accountability; leads data focused internal project team meetings; meets frequently with the study leads of EDC Design, SAS Programming, Statistics, and PK to ensure that all deliverables are planned and coordinated intradepartmental; proactively identifies potential risks/mitigations, effectively communicates data-driven discussions in order to achieve database lock dates; keeps the Project Manager or FSP Lead (or designee) apprised of project progress. • Maintain awareness of other Biometrics functional group deliverables to be able to support risk and mitigation strategies, including impact on DM resources or deliverables and consult with Project Manager (or designee) and/or functional group management as necessary.
