Senior Assistant Vice President

EXL•New York, NY

4h•$173,000 - $175,000

About The Position

Lead high-impact data transformation initiatives for enterprise clients across industries such as sports, healthcare, automotive, and digital marketing. Partner with client executives and business stakeholders to understand strategic objectives and translate them into data-driven analytics solutions. Deliver insights through interactive dashboards, customized reporting, and advanced analytics to guide high-level decision-making. Present recommendations to senior and C-Suite leadership using clear, data-driven storytelling and compelling visualizations. The role leads analytics project delivery and cross-functional teams, architects scalable data ecosystems, and oversees data ingestion, profiling, transformation, and semantic layer development. It applies cloud platforms and advanced statistical and machine-learning methods, operationalizes predictive models, and leads innovation and marketing analytics initiatives. The position also manages and develops a multidisciplinary team and supports talent acquisition. Work may take place at various and unanticipated worksites throughout the United States; telecommuting is permitted.

Requirements

Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or a related analytical field.
Eight years of data analytics, data engineering, or business intelligence experience.
At least seven years of experience with data engineering and ETL development.
At least five years of experience with AWS or Azure cloud platforms.
At least five years of experience with Python, SQL, R, or PySpark.
At least four years of project and people management experience.
At least three years of experience with Power BI or Tableau.
At least two years of data governance and compliance experience.
At least two years of statistical and predictive analytics experience, including machine learning, forecasting, or segmentation.

Responsibilities

Lead end-to-end analytics project delivery, including requirements gathering, scoping, timeline management, and stakeholder communication.
Champion Agile methodologies, including Scrum and Kanban; manage sprints and workflows through JIRA and maintain documentation in Confluence.
Ensure project governance, risk management, and delivery excellence across cross-functional teams.
Architect scalable data ecosystems, including pipelines supporting business intelligence, machine-learning models, and enterprise reporting.
Oversee data ingestion, profiling, transformation, and semantic layer creation to enable efficient analytics consumption.
Use cloud platforms such as AWS and Azure to build secure, scalable environments for data processing.
Evaluate and implement modeling techniques such as ensemble learning, neural networks, time-series forecasting, and multivariate statistics.
Operationalize machine-learning and predictive models in production environments to support automated decision-making.
Lead innovation initiatives using generative AI, optimization methods, and advanced statistical approaches.
Lead marketing analytics initiatives such as media mix modeling, multi-touch attribution, and budget allocation optimization.
Develop performance metrics, predictive models, and analytical insights for sports clients to support game strategy and fan engagement.
Manage, mentor, and develop data engineers, data scientists, BI developers, and project managers.
Drive talent acquisition efforts, including campus hiring, assessments, and onboarding programs.
Foster a culture of continuous learning, innovation, and collaborative problem-solving.