Lead Data Scientist – Vice President

Role Overview

• Define and execute the data analytics strategy, aligning it with overall business objectives and identifying opportunities for leveraging data to gain competitive advantage.
• Lead and oversee multiple complex data analytics projects, ensuring timely delivery, high quality, and measurable business impact.
• Take full ownership of analytical initiatives from problem definition to solution implementation and post-launch evaluation.
• Apply sophisticated statistical analysis, predictive modeling, machine learning techniques, and experimental design (A/B testing) to uncover deep insights, forecast trends, and assess the impact of business decisions.
• Collaborate effectively with senior leadership, cross-functional department heads, and external partners to understand business challenges, articulate analytical solutions, and communicate complex findings and recommendations.
• Provide strong technical and career mentorship to a team of data analysts, fostering their growth, developing their skills, and promoting best practices in data governance, data quality, and analytical methodology.
• Partner with data engineering and IT teams to influence data architecture design, ensure data quality, accessibility, and integrity, and establish robust data governance frameworks.
• Evaluate and recommend new analytical tools, technologies, and methodologies to enhance the team's capabilities and drive continuous innovation in data analytics.
• Design, develop, and implement advanced dashboards, reporting systems, and analytical frameworks to monitor key business performance indicators, identify root causes of performance issues, and recommend optimization strategies.

Requirements

• Bachelor's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Economics, or a closely related discipline.
• A Master's degree or MBA is highly preferred.
• Minimum of 13+ years of progressive experience in data analytics, business intelligence, data science, or a similar data-intensive role, with at least 3-5 years in a leadership or lead analyst capacity.
• Expert-level SQL Proficiency: Demonstrated mastery in writing and optimizing complex SQL queries for data extraction, transformation, and analysis across large-scale data warehouses and databases.
• Advanced Programming Skills: Expert proficiency in at least one major programming language for data analysis (e.g., Python, R), with extensive experience using relevant libraries (e.g., Pandas, NumPy, Scikit-learn, SciPy in Python; tidyverse, ggplot2, caret in R).
• Business Intelligence & Visualization Expertise: Proven track record of designing and implementing executive-level dashboards, interactive reports, and compelling data visualizations using industry-leading BI tools (e.g., Tableau, Power BI, Looker, Qlik Sense) to drive strategic decisions.
• Statistical & Modeling Acumen: Deep understanding and practical application of statistical modeling, hypothesis testing, regression analysis, time series forecasting, and other advanced analytical techniques.
• Cloud Data Platforms: Extensive hands-on experience with cloud-based data platforms and services (e.g., AWS Redshift, S3, Athena, EMR; Google BigQuery, Cloud Dataflow, Cloud Storage; Azure Synapse Analytics, Data Lake) for data storage, processing, and analysis.
• Leadership & Strategic Thinking: Demonstrated ability to lead analytical initiatives, manage complex projects, mentor junior team members, and influence strategic decision-making at a senior organizational level.
• Exceptional Communication: Superior ability to communicate complex technical concepts and analytical insights to both highly technical and non-technical executive audiences through clear, concise, and impactful presentations and written reports.
• Problem-Solving & Critical Thinking: Outstanding analytical and problem-solving skills, with a proven ability to identify root causes, develop innovative solutions, and drive continuous improvement.

Tech Stack

• Amazon Redshift
• AWS
• Azure
• BigQuery
• Cloud
• Numpy
• Pandas
• Python
• Scikit-Learn
• SQL
• Tableau

Benefits

• Health insurance
• Retirement plans
• Paid time off
• Flexible work arrangements
• Professional development
• Bonuses
• Stock options
• Equipment allowances
• Wellness programs