Manager - Data Analytics

As a Manager, Data Analytics, you will lead a critical function within the Data Science team, contributing to a data platform that solves complex challenges for our customers. You will guide a team of data professionals, leveraging your deep analytical skills, business acumen, and creativity to extract insights from massive datasets. This role involves active participation in data usability, standardization, and UAT initiatives, alongside the development and deployment of metrics and analytical solutions to support strategic business decisions.

Responsibilities:

• Team Leadership & Mentorship:

  Lead and mentor a team of data professionals, fostering their growth and ensuring high performance in tackling various analytics problems. Provide thought leadership on complex data challenges.

• Strategic Collaboration:

  Work across cross-functional groups, including business planners and decision-makers, to translate complex business questions into verifiable hypotheses and robust data models.

• Data Infrastructure & Quality:

  Collaborate closely with the data warehousing team, ensuring that the data infrastructure effectively supports the needs of the analytics team and validating data quality rigorously.

• Analytical Solution Development:

  Design and develop data preparation components and processes to extract and transform data across disparate databases for reporting and analytics. This includes developing requirement specifications and assisting with the development and testing of data tables, ensuring the integrity of analysis data.

• Insight Generation & Advocacy:

  Develop clear, concise, and actionable models and recommendations from vast amounts of data. Advocate for the exploration of interesting data anomalies or patterns that could provide deeper explanatory detail about customer behaviors or predictive value to the business.

• Scalability & Efficiency:

  Ensure that all developed analytical solutions are scalable, repeatable, efficient, and effective, meeting high standards of operational excellence.

• Client & Stakeholder Engagement:

  Interact regularly with onsite teams and clients to gather requirements, provide updates, and ensure alignment on project objectives.

• Business Development Support:

  Contribute to the overall growth of the company by providing pre-sales and operational support as needed.

Required Skills:

• Strong analytical and logical thinking capabilities.
• Advanced

  SQL

  skills with database proficiency, including researching and manipulating complex and large datasets (both distributed and non-distributed).
• Proficiency in one or more scripting languages, such as

  Python or Scala

  .
• Proficiency with complex analytical tools, such as

  SAS or R

  .
• Proficiency with data visualization tools, such as

  Tableau, Spotfire, or Qlikview

  .
• Proficiency in statistical techniques such as

  Regression, Clustering, and Time Series Forecasting

  .
• Proven ability to deeply understand data and leverage creative thinking and problem-solving skills to build new data models.
• Strong understanding of data infrastructure, data warehouses, or data engineering principles.
• Ability to coordinate with business planners and decision-makers to translate business questions into verifiable data models and hypotheses.
• Ability to work with engineers to develop, test, and maintain accurate tracking, capturing, and reporting of key data.
• Proficiency in

  MS Excel & PowerPoint

  .
• Excellent communication skills, both written and verbal.