About this 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)
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