Job Summary :
We are looking for a highly skilled and results-driven Data Scientist to join our data and analytics team. The ideal candidate will be responsible for designing and implementing advanced machine learning and AI models to solve real-world business problems. You will work closely with cross-functional teams to gather data, build predictive and prescriptive models, and communicate insights that inform strategic decisions. Your expertise will help drive innovation and data-driven transformation across the organization.
Key Responsibilities :
- Collect, clean, and preprocess structured and unstructured data from diverse internal and external sources.
- Perform data wrangling, missing value imputation, feature engineering, and data transformation to prepare datasets for analysis and modeling.
- Work with large-scale datasets from relational databases, APIs, cloud sources, or raw files (e.g., CSV, JSON, logs, text).
Develop and deploy machine learning (ML) and AI models for :
Classification, regression, clusteringRecommendation systemsAnomaly detection and forecasting (as needed)Perform model selection, hyperparameter tuning, cross-validation, and evaluation using best practices.Use AWS SageMaker, H2O.ai, or in-house tools to train, evaluate, and deploy models at scale.Package and deploy models as APIs or batch processes, integrating them into business workflows or applicationsApply descriptive statistics, inferential statistics, and hypothesis testing to derive insights from data.Design experiments (e.g., A / B testing) and analyze their results.Translate business challenges into quantitative frameworks and model-driven solutions.Continuously track model performance (e.g., drift, degradation, real-world impact).Re-train, re-tune, or retire models as needed to maintain accuracy and relevance.Implement model versioning, logging, and audit trails for traceability.Work with stakeholders from product, marketing, engineering, and business teams to understand needs and define solutions.Present analytical results, data-driven recommendations, and visualizations to non-technical audiences.Document solutions, processes, assumptions, and results clearly and concisely.Required Skills & Qualifications :
3 - 6 years of experience in a Data Science or Machine Learning role.Strong programming skills in Python, including libraries such as :
NumPy, pandas, scikit-learnmatplotlib, seaborn (for visualization)Solid command of SQL for querying, transforming, and analyzing data from relational databases.Experience deploying models using AWS SageMaker or similar cloud platforms.Familiarity with H2O.ai tools and automated machine learning (AutoML) frameworks.Strong understanding of statistical theory, data distributions, bias / variance trade-offs, and model evaluation metrics.Proficiency in the full ML lifecycle : from data exploration and feature engineering to deployment and monitoring.(ref : hirist.tech)
