Summary:
The Principal Data Scientist will be a senior technical leader and individual
contributor responsible for tackling our most challenging data science problems.
This individual will leverage their deep expertise in statistical modeling,
machine learning, and data analysis to extract actionable insights from complex
datasets and drive data-informed decision-making across the organization. The
ideal candidate is a creative problem-solver with a passion for turning data
into value. This role requires working closely with business partners while
understanding and working within the constraints of the business.
Duties and Responsibilities:
Lead complex data science projects from conception to completion, working
with large and diverse datasets.
Apply advanced statistical and machine learning techniques to build
predictive models, conduct in-depth analyses, and generate actionable
insights.
Collaborate with cross-functional teams, including product, engineering, and
business stakeholders, to identify and solve key business problems.
Mentor and provide technical guidance to other data scientists and analysts
on the team.
Communicate complex findings and recommendations to both technical and
non-technical audiences.
Stay current with the latest data science tools and techniques and champion
their adoption within the organization.
Influence product and operational roadmap with actionable insights and active
deployments.
Discover key drivers of the business in a team and as an individual
contributor.
Develop measurement strategy for scoped areas – deploying best principles
around experiment design and statistical analysis
Build a strategic learning roadmap based on data observations, strategic
imperatives and developed hypotheses
Experience managing data pipelines.
Minimum Qualifications:
Master's degree or equivalent in experience in a quantitative field such as a
Computer Science, Statistics, Mathematics or a related discipline.
8+ years of hands-on experience in data science, with a strong portfolio of
completed projects.
Expertise in statistical modeling, machine learning, and data mining
techniques.
Proficiency in programming languages such as Python or R, and experience with
data science libraries and tools (e.g., Scikit-learn, Pandas, Spark).
Strong problem-solving skills and the ability to think creatively and
strategically.
Excellent communication and collaboration skills.
Proven track record of delivering at least two major data products that
resulted in measurable business growth or cost savings.
Communication Skills:
Writing, Talking/Hearing on the phone (Continually=67-100% of workday)
Environment Requirements:
Remote/Home office (Continually=67-100% of the workday)