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Senior Data Science Lead
Primary Skills
- Data Scientist
- Skills:
- Familiarity with cloud platforms such as AWS, Azure, or GCP for data processing and analytics.
• Translate complex business problems into structured, data- and model-driven narratives. Partner with stakeholders to frame ambiguous problem statements, perform deep exploratory Data Analysis (EDA), Visualizations, Hypothesis A/B Testing/ What-if analysis and scenario modeling, Algorithm development to identify inefficient sectors (DL/UL) by flagging outliers using performance KPIs.
• Communicate statistically sound, model-backed insights that directly influence strategic and operational decisions.
• Apply advanced statistical techniques, classical ML, and modern AI approaches to forecast outcomes and recommend next-best actions.
• Experience in driving initiatives through a rigorous lifecycle—problem formulation → hypothesis generation → EDA → feature engineering → modeling → evaluation → visualization → measurable business impact—ensuring scientific rigor, interpretability, and alignment with business objectives.
• Develop, evaluate, and iterate on analytical, machine learning, and hybrid AI models to uncover patterns, trends, and anomalies, solving complex problems such as churn prediction, revenue optimization, network efficiency, and operational optimization.
• Demonstrate strong hands-on expertise in BigQuery, SQL, and Python to build scalable data pipelines, feature stores, and analytical workflows, ensuring performance, reproducibility, and accuracy on large-scale datasets.
• Ensure consistency and reliability across diverse data sources through strong data validation, monitoring, and governance practices. Maintain trust in analytical and AI-driven outcomes through robust data quality checks, model validation, and ongoing performance monitoring.
• Collaborate with cross-functional teams (data engineering, SRE, platform, and business teams) to operationalize AI-driven insights, ensure reliability, and deliver measurable business impact.
• Drive continuous improvement initiatives by integrating feedback loops, monitoring KPIs on data reliability aligned to enterprise goals.
• Mentorship & Collaboration – Guide junior analysts, promote knowledge sharing, and foster a culture of analytical excellence across teams.
• Analytical Mindset & Self-Starter – Proactive in identifying opportunities, framing problems, and communicating insights in a business-first language, bridging the gap between data science and strategy.
• Data Visualization & Dashboards – Transform raw numbers into intuitive dashboards and visual stories that resonate with both technical and non-technical audiences, enabling faster decisions.
• Strong proficiency in Advanced SQL with experience in writing optimized queries for large datasets.
• Expertise in data analytics with a solid understanding of statistical methods and data interpretation.
• Exposure to Data Science concepts, including predictive modeling and machine learning techniques.
• Hands-on experience with Python, R, or similar analytical tools is a plus.
• Experience working with large-scale datasets and business intelligence tools.
• Strong problem-solving abilities with the capability to translate business problems into analytical solutions.
• Excellent communication and presentation skills to convey insights effectively to stakeholders.
Specialization
- Data Science Advanced: Data Science Lead
Job requirements
- Data Science Advanced: Data Science Lead
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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