Senior Data Scientist

6 days ago

Bengaluru, India Marktine Technology Solutions Full time

KEY RESPONSIBILITIES :- Develop, validate, and deploy predictive, prescriptive, and scoring models to power product features and business decisions.- Partner with the product management and data engineering teams to design and implement algorithms that directly impact customer experience and business growth.- Drive feature engineering, model selection, and performance evaluation across diverse modeling use cases (scoring, forecasting, optimization, segmentation, simulation, NLP, etc.).- Make analytical and technical decisions on modeling trade-offs (accuracy, interpretability, scalability).- Ensure models are production-grade, explainable, monitored, and continuously improved as data and market conditions evolve.- Stay up to date with emerging ML/AI techniques and proactively evaluate their applicability to business use cases.REQUIRED SKILLS :- Strong foundation in Machine Learning, Statistical Modeling, and Applied Mathematics, with proven experience in real-world problem-solving.- Hands-on expertise in Python and R, including ML libraries (scikit-learn, XGBoost, PyTorch/TensorFlow for deep learning)- Solid understanding of data preprocessing, feature engineering, and handling large-scale structured and unstructured datasets.- Experience in building and deploying models such as : Scoring/response models, recommendation systems, forecasting, optimization, segmentation, causal inference.- Excellent communication and stakeholder management skills, with the ability to effectively influence, align, and drive consensus across product, engineering, and business teams.- Proven track record of leading analytics/modeling projects end-to-end.DESIRED SKILLS :- Exposure to Text Mining and NLP (topic modeling, sentiment analysis, embeddings)- Knowledge of LLM-based applications is a plus.- Knowledge of Bayesian analysis and probabilistic modeling.- Experience with optimization algorithms, reinforcement learning, or simulation modeling.- Working knowledge of cloud platforms (AWS) and ML pipelines is a plus.- Exposure to Deep Learning- Familiarity with digital marketing, SEO, and search-related modeling is a plus.QUALIFICATIONS :- Master's or PhD in a quantitative field (Computer Science, Statistics, Applied Mathematics, Data Science, Operations Research, Economics, Engineering).- 4-6 years of experience in applied data science/modeling, ideally with projects spanning predictive modeling, NLP, optimization, and business-focused analytics.- Experience delivering models into production environments (not just research/prototyping). (ref:hirist.tech)

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