Product Manager – Data Science / Data Solutions at WTW
Calgary, AB, Canada -
Full Time


Start Date

Immediate

Expiry Date

22 Oct, 25

Salary

0.0

Posted On

22 Jul, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Architecture, Computer Science, Data Engineering, Operational Efficiency, Cost Efficiency, Analytics, Project Management Skills, Scalability, Azure, Business Analytics, Python

Industry

Information Technology/IT

Description

DESCRIPTION

As a Product Manager – Data Science, you will contribute to the strategic direction and execution of data science initiatives, leveraging your extensive experience in data engineering and analytics. You will drive initiatives that use innovative technologies to deliver data-driven insights and solutions, ensuring they align with business goals and maintain cost efficiency. This role demands a strong background in data consulting, architecture and strategy, as well as the ability to act as an effective liaison between technical teams and business stakeholders.

REQUIREMENTS AND SKILLS:

  • Bachelor’s Degree in Business Analytics, Computer Science or a related field, with additional certifications in data and analytics preferred.Strong experience in data engineering and architecture, particularly with Databricks, Azure, PowerBI, Python and SQL.Proven track record in managing data-driven projects end-to-end, with an emphasis on scalability, parallel performance, and cost-efficiency.
  • Skilled in data consulting and translating complex technical concepts for non-technical audiences.
  • Excellent project management skills, with the ability to meet expectations and maintain operational efficiency.
  • Excellent communication and data storytelling skills, with the ability to translate complex data insights into business strategies.
    Equal Opportunity Employe
Responsibilities
  • Lead and oversee the development, implementation and enhancement of data science and engineering initiatives, ensuring alignment with business objectives and timelines.
  • Translate business requirements into clear, actionable technical specifications.
  • Facilitate communication between technical teams and business units, ensuring alignment of expectations and objectives.
  • Participate in the end-to-end management of the data science product lifecycle, from ideation through deployment to performance monitoring.
  • Drive cross-functional collaboration between data engineering, architecture and data science, promoting seamless communication and strategic alignment.Stay abreast of industry trends and emerging technologies in data science and AI, integrating these into product strategy and delivery.
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