Data Science Specialist

6 days ago

Hyderabad, Telangana, India Re Sustainability Limited Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Key Responsibilities

  1. Business & Strategy Alignment

  2. Business Translation:
    Proactively engage with business stakeholders, product managers, and domain experts to deeply understand key organizational challenges and strategic goals.

  3. Solution Design:
    Formulate and scope data science initiatives, defining clear objectives, success metrics, and a technical roadmap that directly addresses identified business requirements.

  4. End-to-End Model Development & Deployment

  5. Algorithm Development:
    Design, prototype, build, and validate machine learning and statistical models from scratch, without reliance on pre-packaged solutions.

  6. Production Deployment:
    Implement and manage MLOps pipelines within
    Azure Machine Learning
    to ensure reproducible model training, versioning, testing, and continuous deployment into live operational environments.

  7. Infrastructure:
    Collaborate with DevOps and engineering teams to ensure algorithms run efficiently and scale reliably within the cloud environment.

  8. Data Engineering & Feature Management

  9. Data Crunching and Manipulation:
    Execute complex data ingestion, exploration, and feature engineering tasks, applying rigorous statistical methods and domain knowledge to raw and disparate datasets.

  10. Quality & Integrity:
    Ensure data integrity throughout the modeling lifecycle, performing extensive Exploratory Data Analysis (EDA) and cleaning to prepare high-quality inputs.

  11. Advanced AI & Innovation (Preferred/Plus)

  12. Generative AI:
    Explore, experiment with, and deploy large language models (LLMs) and other Gen AI techniques to create new products or optimize existing processes (e.g., semantic search, content generation, synthetic data creation).

  13. Agentic AI Systems:
    Investigate and prototype intelligent software agents capable of autonomous decision-making, planning, and tool use, moving beyond simple predictive models.

  14. Code Quality & Collaboration

  15. Write clean, well-documented, and efficient
    Python code
    , adhering to software engineering best practices, including unit testing and code reviews.

  16. Mentor junior team members and contribute to the growth of the team's overall ML/AI knowledge base.

Required Qualifications

  • Education:
    Master's degree or higher in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Programming Mastery:
    5+ years of professional experience leveraging
    Python
    for data science, including deep expertise in the PyData stack (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
  • Cloud ML Platforms:
    Proven, hands-on experience building and managing ML models and MLOps workflows specifically using
    Azure Machine Learning
    services (e.g., Azure ML Pipelines, Endpoints, Datastores).
  • Statistical Rigor:
    Strong background in statistical modeling, experimental design (A/B testing), and model validation techniques.
  • Data Skills:
    Expert proficiency in SQL and experience working with large-scale, high-velocity data, including ETL/ELT processes and data visualization.

Preferred Qualifications (A Significant Plus)

  • Generative AI Experience:
    Practical experience fine-tuning, RAG-ifying, or deploying modern Large Language Models (LLMs) (e.g., OpenAI, Gemini, Llama).
  • Agent Development:
    Knowledge of agentic frameworks (e.g., LangChain, LlamaIndex) and experience designing multi-step, tool-using autonomous AI workflows.
  • Experience with other cloud platforms (AWS Sagemaker, GCP Vertex AI) is beneficial.
  • Demonstrated ability to write production-level, highly optimized code for critical systems.

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