Assistant Manager - Data Scientist

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, Num.

Py, 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, Tensor. Flow, or Py. Torch ● 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)