Job Summary
as needed.
Business Problem Solving
Translate business requirements into analytical solutions.
Present findings and recommendations to stakeholders in clear, actionable formats.
Collaboration & Communication
Work closely with data engineers, analysts, and product teams to integrate models into production systems.
Communicate technical concepts to non-technical audiences.
Tooling & Automation
Develop reusable code and pipelines for data processing and model training.
Use version control and CI/CD tools to manage model lifecycle.
Requirements
Required Qualifications & Skills
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
3–5 years of experience in data science or machine learning roles.
Proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch).
Experience with SQL, data visualization tools (e.g., PowerBI, Tableau), and cloud platforms (AWS, Azure, GCP).
Strong understanding of statistical methods, data modeling, and machine learning algorithms.
Familiarity with Databricks, Jupyter Notebooks, and ML Ops practices.
Excellent problem-solving, communication, and stakeholder engagement skills.
Desirable Skills
Experience with big data tools (Spark, Hadoop).
Knowledge of NLP, time-series forecasting, or deep learning.
Exposure to data governance, privacy, and compliance frameworks.
Prior experience in financial services, healthcare, or retail analytics.
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