Product Data Scientist
About The Position
About The Weather Company: The Weather Company is the world’s leading weather provider, helping people and businesses make more informed decisions and take action in the face of weather. Together with advanced technology and AI, The Weather Company’s high-volume weather data, insights, advertising, and media solutions across the open web help people, businesses, and brands around the world prepare for and harness the power of weather in a scalable, privacy-forward way. The world’s most accurate forecaster globally, the company reaches hundreds of enterprise clients and more than 360 million monthly active users via its digital properties from The Weather Channel (weather.com) and Weather Underground (wunderground.com). Job brief: We’re looking for a Senior Data Scientist to partner closely with Product, Engineering, and Design teams to drive data-informed product decisions. In this role, you’ll translate complex product questions into analytical frameworks, build models and experiments, and deliver insights that influence strategy and roadmap priorities. You’ll also play a key role in technical leadership, mentoring, and shaping best practices across the data science function. The impact you'll make: Partner with Product, Engineering, and Design to define success metrics and translate product questions into complex analytical frameworks. Develop and maintain models, dashboards and reports to establish and monitor key metrics and performance indicators. Drive innovation and testing to support strong strategic product decision making. Develop statistically sound hypotheses and communicate experiment results with clear recommendations. Establish best practices for experimentation, including power analysis and metric selection. Present findings and insights to senior management and other key stakeholders. Design and implement data collection systems and other strategies to optimize statistical efficiency and data quality. Leads technical decisions for multiple projects while collaborating with cross-functional teams. Guides and approves feature engineering and model architecture choices. Conducts and leads model reviews and validation processes for quality assurance. Provides technical guidance and mentorship to data science teams and junior scientists in best practices and technical development.
Requirements
- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or a related STEM field.; or commensurate experience.
- 5+ years of professional experience in data science, machine learning, or a related field.
- Expert-level Python and proficiency in multiple ML frameworks and languages
- Strong understanding of advanced ML/DL architectures and system design
- Experience with cloud ML platforms (SageMaker, Vertex AI) and distributed computing for ML
- Experience with quant analysis for A/B/n and multivariate experiments
- Understanding of statistical methods and quasi-experimental designs for analytical problems
- Demonstrated experience with ML documentation and advanced technical communication
- Technical leadership and mentoring abilities
- Project planning and execution skills
- Demonstrated capability in cross-functional collaboration and team leadership
- Demonstrated experience developing, presenting and influencing strategic decision making
Nice To Haves
- Experience with developing and deploying AI training and inference pipelines
- Experience with building Generative AI, Text to Speech, and Speech to Text solutions
- Experience providing architecture to drive product decision-making
Responsibilities
- Partner with Product, Engineering, and Design to define success metrics and translate product questions into complex analytical frameworks.
- Develop and maintain models, dashboards and reports to establish and monitor key metrics and performance indicators.
- Drive innovation and testing to support strong strategic product decision making.
- Develop statistically sound hypotheses and communicate experiment results with clear recommendations.
- Establish best practices for experimentation, including power analysis and metric selection.
- Present findings and insights to senior management and other key stakeholders.
- Design and implement data collection systems and other strategies to optimize statistical efficiency and data quality.
- Leads technical decisions for multiple projects while collaborating with cross-functional teams.
- Guides and approves feature engineering and model architecture choices.
- Conducts and leads model reviews and validation processes for quality assurance.
- Provides technical guidance and mentorship to data science teams and junior scientists in best practices and technical development.
Benefits
- Flexible Time Off program
- Hybrid work model
- Variety of medical insurance options, including a $0 cost premium employee coverage
- Benefits effective day 1 of employment include a competitive 401K match with no vesting requirement, national health, dental, and vision plans
- Progressive family plan benefits
- An opportunity to work for a global and industry-leading technology company
- Impactful work in a collaborative environment
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
