VP, Team Manager (Data Science) [Gartner ๐Ÿ“‹]

:handshake: Company


:briefcase: Title

VP, Team Manager (Data Science)

:incoming_envelope: Apply here

:round_pushpin: Location

Remote โ€“ USA

:building_construction: Job Description

What Youโ€™ll Do

  • Create a strategy and overall vision for where and how data science can further development of scaled insights for our clientsโ€™ most critical needs. A few potential projects or domains you may get involved with:
    • Applying Natural Language Processing (NLP) to classify content created by/and-or about brands
    • Delivering dashboards (Tableau) and web apps (Streamlit) for self-service insights for domains like Social Media and Search Marketing
    • Creating contextual word embedding models/packages to accelerate development of existing and new tools
    • Ingesting and delivering insights from new external data assets in collaboration with Product and Engineering teams
  • Manage Data Science team operations and talent development
  • Identify new data sources that could add value to our research practice
  • Work with data engineers and product managers to develop analytics and ML pipelines to support scalable analysis and internal tools
  • Partner directly with peer managers in Product and Survey Analytics to align user & client needs with the Data Science team
  • Partner closely with Global Product Management (Customer & Market Research) to deliver insights to the practice and support product development, research agendas, and sales enablement

What Youโ€™ll Need

  • Bachelors in a quantitative research field (e.g., Computer Science, Electrical Engineering, Applied Mathematics, Physics, etc.).
  • 10 + years of total experience, including 3-5 years progressive hands-on experience building predictive models, recommendation systems, and/or NLP/text mining tools.
  • 2+ years of experience managing a team of junior data scientists
  • Experience managing a budget
  • Well-versed in the foundational approaches to the major data science disciplines, such as data preparation, advanced statistics, machine learning, data pipelining and natural language processing
  • Practical, intuitive problem solver with a demonstrated ability to translate business objectives into actionable data science tasks and translate quantitative analysis into actionable business strategies
  • Connections to the external ML/Data Science community
  • Experience and proficiency with various programming languages (Python), machine learning models (transformers), statistical packages, SQL/relational databases, and cloud computing (AWS, GCP)
  • Experienced in new product development and product development lifecycle, including product strategy, development, and launch.