Data Science Engineer

1 day ago

Pune, Maharashtra, India RadarSoft Technologies Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Job Title:
Data Science Engineer

Location:
Pune (Onsite)

Employment Type:
Full-Time

Experience:
5+ Years

Notice Period:
Immediate Joiners Preferred

Job Summary:

As a
Data Science Engineer
, you will design, develop, and optimize end-to-end data and machine learning pipelines. You will collaborate with data engineers, analysts, and business teams to ensure scalable and reliable infrastructure supporting AI and advanced analytics initiatives.

Roles and Responsibilities:

  • Design and develop scalable data science and ML pipelines using Python, SQL, and cloud technologies.
  • Implement, train, and deploy machine learning models for predictive and analytical use cases.
  • Collaborate with data engineering teams to ensure data quality, consistency, and availability for modeling.
  • Perform exploratory data analysis (EDA), feature engineering, and data validation.
  • Optimize ML model performance and automate retraining workflows.
  • Integrate AI solutions into production systems and ensure model monitoring and maintenance.
  • Document data workflows, model architecture, and best practices.

Qualifications and Skills:

  • 5+ years of hands-on experience in Data Science, ML Engineering, or Advanced Analytics.
  • Strong programming skills in
    Python
    (Pandas, NumPy, Scikit-learn, etc.) and
    SQL
    .
  • Solid understanding of
    machine learning algorithms
    , statistical modeling, and data preprocessing.
  • Experience in
    ETL / ELT development
    and working with
    data warehousing concepts
    .
  • Proficiency with tools like
    Airflow
    ,
    TensorFlow
    ,
    PyTorch
    , or
    MLflow
    is a plus.
  • Exposure to
    cloud platforms (GCP, AWS, or Azure)
    and CI/CD for ML pipelines.
  • Strong problem-solving, analytical, and debugging skills.

Preferred Skills

  • Experience with
    BigQuery
    ,
    Dataflow
    , or
    Azure ML / AWS SageMaker
    .
  • Familiarity with
    data lake architectures
    ,
    API-based data ingestion
    , and
    containerization (Docker/Kubernetes)
    .
  • Exposure to
    MLOps
    tools and practices.

To Apply:

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