VP, Team Manager (Data Science)
Remote – USA
What You’ll Do
- Create a strategy and overall vision for where and how data science can further development of scaled insights for our clients’ 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 You’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.