Website:
Job details:
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)
Click on Apply to know more.
