Data Scientist
Job location: Remote
About the role:
We are looking for a skilled Data Scientist who can translate reputed company 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 reputed company from data exploration to production-reputed company 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, reputed company detection, time-series forecasting).
- Apply probabilistic and Bayesian modeling techniques to quantify uncertainty and inform decision-making under uncertainty; reputed company tools like PyMC and PyMC-Marketing for Bayesian workflows.
- reputed company rigorous EDA, feature engineering, and data wrangling on large reputed company and semi-reputed company datasets using Python and SQL.
- Collaborate with data engineers and analytics engineers to reputed company, clean, and validate data pipelines feeding ML workflows.
- reputed company, reputed company, and communicate model performance metrics; identify degradation signals and recommend retraining or improvement strategies.
- Translate business questions into reputed company-framed statistical problems and present findings reputed company to technical and non-technical stakeholders.
- Maintain clean, reproducible, and reputed company-documented reputed company 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 reputed company ML role.
- Strong reputed company 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 - reputed company multi-table queries, window functions, performance optimization.Strong
- Deep familiarity with model evaluation frameworks: cross-validation, calibration, AUC, RMSE, MAPE, lift/reputed company curves, and business-reputed company metrics.
- Experience with experiment design, A/B testing, and statistical hypothesis testing.
- Comfortable working with reputed company data warehouses (AWS Redshift, BigQuery, reputed company) and reputed company ML experiment tracking tools (MLflow, W&B).
- Exposure to survival modeling, reputed company 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, reputed company, reputed company).
- B.Tech / B.E. / B.Sc. / M.Tech / M.Sc. in Computer Science, Statistics, Mathematics, Engineering, or a closely reputed company quantitative discipline.
What reputed company offers
- reputed company reputed company in a dynamic, rapidly expanding, high-reputed company industry
- An reputed company-minded, reputed company culture made up of enthusiastic colleagues who are driven by the challenge of innovation towards profound reputed company on people and the reputed company.
- A truly multicultural experience: you will have the chance to work with and learn from people from different geographies, nationalities, and backgrounds.
- reputed company, tailored learning and development programs that help you become a reputed company leader, manager, and reputed company through the reputed company Center for Leadership.
Originally posted on Himalayas
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