The Data Scientist role focuses on extracting actionable insights from large and complex datasets to inform strategic decisions across marketing, product, and operations. This position involves the end-to-end lifecycle of data modeling—from data collection and cleaning to feature engineering, algorithm selection, and model deployment. Data Scientists work closely with stakeholders to translate business questions into analytical solutions and communicate findings in a clear, compelling manner.

Key Responsibilities:

• Design and implement data pipelines to ingest, clean, and transform structured and unstructured data
• Perform exploratory data analysis to identify trends, anomalies, and opportunities for optimization
• Develop and validate predictive models (classification, regression, clustering) using Python, R, or similar tools
• Engineer features and select appropriate algorithms (e.g., tree-based methods, neural networks, NLP) to maximize model performance
• Deploy models into production environments or BI platforms, collaborating with MLOps or engineering teams
• Visualize results and build interactive dashboards (Tableau, Looker, Power BI) to make insights accessible to non-technical stakeholders
• Present analytical findings, model interpretations, and business impact recommendations to cross-functional teams

Successful candidates will also stay up to date on the latest machine-learning research, contribute to code reviews and best practices, and mentor junior analysts when needed.

Qualifications & Skills:

• 3+ years of hands-on experience in data science, analytics, or a related role
• Proficiency in programming languages such as Python or R and libraries like pandas, scikit-learn, TensorFlow, or PyTorch
• Strong SQL skills for querying relational databases and experience with big-data tools (Spark, Hive) a plus
• Deep understanding of statistical methods, hypothesis testing, and experimental design
• Excellent data visualization skills and familiarity with BI tools (Tableau, Looker, Power BI)
• Strong problem-solving abilities and comfort working with ambiguous, unstructured data
• Effective communication and storytelling skills to translate complex analyses into clear business insights

Performance in this role is measured by model accuracy, deployment success rate, impact on key business metrics (e.g., increased revenue, reduced churn), and the ability to drive data-driven decisions across the organization.

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