About the role
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)