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CarWale - Senior Data Scientist - Machine Learning

CarWale - Senior Data Scientist - Machine Learning

ConfidentialNavi Mumbai, Mumbai, India
4 days ago
Job description

Description

Senior Data Scientist (Machine Learning Engineer)

Role Overview

We are seeking a highly skilled Senior Data Scientist / Machine Learning Engineer to design, build, and deploy advanced machine learning and generative AI solutions that drive business value. This role blends deep technical expertise with strategic thinking, requiring hands-on experience in data science, software engineering, and MLOps.

Key Responsibilities

Machine Learning & Data Science :

  • Design, develop, and deploy advanced machine learning and statistical models to address complex business problems.
  • Build, optimize, and maintain end-to-end ML pipelines, including data ingestion, preprocessing, feature engineering, model training, evaluation, and production deployment.
  • Lead Generative AI initiatives, leveraging LLMs, diffusion models, and other modern architectures to develop innovative solutions.
  • Conduct deep-dive analyses on large and complex datasets to extract actionable insights and recommendations.
  • Collaborate with cross-functional teams (Engineering, Product, and Business) to align data-driven initiatives with organizational goals.

Engineering & Development

  • Write clean, efficient, and maintainable code in Python and at least one additional language (e.g., C#, Go, or Java).
  • Implement strong software engineering practices, including version control (Git), CI / CD, testing, and containerization (Docker, Kubernetes).
  • Participate in code and model reviews, ensuring adherence to best practices and scalability standards.
  • Integrate models into production systems using MLOps tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI).

    • Innovation & Continuous Improvement

  • Stay up to date with the latest developments in Machine Learning, Generative AI, and MLOps frameworks and methodologies.
  • Proactively identify opportunities to enhance existing systems and develop new data-driven solutions.
  • Maintain detailed documentation for models, workflows, and experiments to ensure transparency and reproducibility.

    • Skills & Qualifications

    Education :

  • Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, Statistics, or a related quantitative field (PhD preferred).

    • Experience

  • 6+ years of hands-on experience in Data Science and Machine Learning roles, with proven experience deploying models to production.
  • Demonstrated experience in designing and implementing ML solutions at scale (preferably in cloud environments such as AWS, Azure, or GCP).
  • Proven track record of working on Generative AI or LLM-based projects is a strong plus.

    • Technical Skills

  • Programming : Proficiency in Python (pandas, NumPy, scikit-learn, PyTorch, TensorFlow); experience with one or more additional languages (e.g., C#, Go, Java).
  • Machine Learning : Strong understanding of supervised, unsupervised, and deep learning methods; experience with NLP, computer vision, or generative modeling is desirable.
  • Data Engineering : Experience with SQL, data pipelines, and ETL frameworks (e.g., Airflow, dbt, Spark).
  • MLOps : Hands-on experience with MLflow, Kubeflow, AWS SageMaker, Vertex AI, or equivalent tools for model tracking and deployment.
  • Generative AI : Experience with LLM fine-tuning, embeddings, prompt engineering, and vector databases (e.g., Pinecone, FAISS, Chroma).
  • Cloud & DevOps : Familiarity with cloud platforms (AWS, Azure, GCP), containerization (Docker), and orchestration (Kubernetes).
  • Visualization : Proficiency with tools like Power BI, Tableau, or Plotly for communicating insights.

    • Soft Skills

  • Excellent communication and collaboration skills, with the ability to translate technical findings into business value.
  • Strong problem-solving, analytical, and critical-thinking abilities.
  • Ability to mentor junior team members and contribute to a culture of innovation and excellence.

    • Preferred Qualifications

  • Experience in building AI-powered applications or products.
  • Publications, patents, or open-source contributions in ML / AI.
  • Familiarity with data governance, model interpretability, and responsible AI principles.

    • (ref : hirist.tech)

    Skills Required

    Airflow, Go, Tableau, Tensorflow, Numpy, Pytorch, Docker, Python, Aws, Java, Power Bi, Sql, Pandas, dbt, Spark, Kubernetes

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