Data Scientist Principal

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)