Manager-Data Scientist
7 days ago
Responsibilities:
- Lead a team of 1-3 data scientists working across agile pods
- Lead your team in complex data science projects, working closely with stakeholders to identify opportunities and develop solutions that drive business value.
- Develop, test, and deploy predictive models using machine learning and statistical techniques
- Collaborate with stakeholders to identify opportunities and design solutions
- Explore and analyze large datasets to inform business decisions
- Create repeatable, interpretable, and scalable models and statistical products
- Engineer new features and test various modeling approaches to develop industry-leading analytics products
- Contribute to the development of our data science capabilities and best practices
- Communicate complex technical concepts to non-technical stakeholders, including data insights and recommendations
- Stay up-to-date with industry trends and emerging technologies in data science, making recommendations for how to leverage these advancements to drive business growth
- Coach and develop your team, driving technical best practices and contributing to their career growth within data science
Requirements:
- Master’s degree in Data Science, Computer Science, Engineering, or Statistics
- 5+ years of applied experience in data science or related field
- Expertise in implementing ML and AI algorithms in Python and/or R
- Fluency in SQL
- Strong understanding of machine learning, data wrangling, and exploratory analysis
- Ability to work collaboratively with stakeholders to deliver high-impact results
- Excellent communication and problem-solving skills
Preferred Qualifications:
- Prior people management experience
- Experience with Big Data technologies such as Snowflake and Spark
- Experience with cloud-based technologies such as Azure
- Familiarity with Agile development methodologies
- Experience working in a cross-functional team environment
- Expertise with the following modeling methods: Design of Experiments, ANOVA, multivariate regression, discrete and continuous optimization, survival analysis, discrete event simulation
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