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Assistant Manager - Data Scientist

Chennai, India

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Employment
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Tools in this posting

  • Python
  • SQL
  • AWS
  • Azure
  • Docker
  • Spark
  • pandas
  • TensorFlow
  • Xgboost
  • R
  • Hadoop
  • Google Cloud (GCP)
  • Power BI
  • Tableau
  • Kubernetes
  • MLflow
  • NumPy
  • Matplotlib
  • scikit-learn
  • PyTorch
  • Airflow
Source — Tool mentions in context
● 8+ years of hands-on experience in data science, applied machine learning, or a similar analytical role ● Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and/or R ● Solid understanding of statistics, probability, and experimental design
● Solid understanding of statistics, probability, and experimental design ● Experience with SQL and working with relational/non-relational databases ● Hands-on experience with ML frameworks such as Scikit-learn, XGBoost, TensorFlow, or PyTorch
● Experience with data visualization tools (Tableau, Power BI, or Matplotlib/Seaborn) ● Familiarity with cloud platforms (AWS, GCP, or Azure) for model deployment ● Strong problem-solving skills and ability to work with ambiguous business problems
● Excellent communication skills to present technical findings to non-technical audiences ● Experience with MLOps tools (MLflow, Airflow, Docker, Kubernetes) ● Exposure to NLP, computer vision, or time-series forecasting
● Experience working in Agile/Scrum environments ● Knowledge of big data tools (Spark, Hadoop)
● Experience with SQL and working with relational/non-relational databases ● Hands-on experience with ML frameworks such as Scikit-learn, XGBoost, TensorFlow, or PyTorch ● Experience with data visualization tools (Tableau, Power BI, or Matplotlib/Seaborn)
● Hands-on experience with ML frameworks such as Scikit-learn, XGBoost, TensorFlow, or PyTorch ● Experience with data visualization tools (Tableau, Power BI, or Matplotlib/Seaborn) ● Familiarity with cloud platforms (AWS, GCP, or Azure) for model deployment

Job description

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Assistant Manager – Data Scientist

We are looking for an experienced Data Scientist to join our team and drive data-driven decision-making across the organization. The ideal candidate will have a strong foundation in statistical analysis, machine learning, and business problem-solving, with proven experience translating data into actionable insights.

Key Responsibilities

●      Design, build, and deploy machine learning models to solve business problems (classification, regression, clustering, recommendation systems, etc.)

●      Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies in large datasets

●      Collaborate with product, engineering, and business teams to define data science use cases and success metrics

●      Develop and maintain data pipelines in partnership with data engineering teams

●      Conduct A/B testing and statistical experiments to validate hypotheses and measure impact

●      Communicate findings and recommendations to both technical and non-technical stakeholders through reports, dashboards, and presentations

●      Own end-to-end model lifecycle: from data collection and feature engineering to model deployment and monitoring

●      Stay current with the latest research and best practices in data science and machine learning

●      Mentor junior data scientists/analysts as needed

 

Required Skills & Qualifications

●      Bachelor's/Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related field

●      8+ years of hands-on experience in data science, applied machine learning, or a similar analytical role

●      Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and/or R

●      Solid understanding of statistics, probability, and experimental design

●      Experience with SQL and working with relational/non-relational databases

●      Hands-on experience with ML frameworks such as Scikit-learn, XGBoost, TensorFlow, or PyTorch

●      Experience with data visualization tools (Tableau, Power BI, or Matplotlib/Seaborn)

●      Familiarity with cloud platforms (AWS, GCP, or Azure) for model deployment

●      Strong problem-solving skills and ability to work with ambiguous business problems

●      Excellent communication skills to present technical findings to non-technical audiences

●      Experience with MLOps tools (MLflow, Airflow, Docker, Kubernetes)

●      Exposure to NLP, computer vision, or time-series forecasting

●      Experience working in Agile/Scrum environments

●      Knowledge of big data tools (Spark, Hadoop)

 



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Chennai, India

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Status in our records
Active
First seen by us
Aug 12, 2026
Recorded sightings
19
Last seen by us
Oct 2, 2026

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