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Senior Data Scientist - Machine Learning / Statistical Modeling

Senior Data Scientist - Machine Learning / Statistical Modeling

Marktine Technology SolutionsBangalore
19 days ago
Job description

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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