[Hiring] Data Scientist @SharkNinja

The Role

As a Data Scientist supporting our Market Insights & Analytics organization, you’ll build and deploy advanced models and analytical capabilities that unlock commercial growth opportunities. You’ll work at the intersection of data, technology, and business — helping SharkNinja turn information into impact across our Sales, Category, and Marketing teams.

Here’s What You’ll Do

• Design, build, and deploy predictive and prescriptive models (forecasting, elasticity, segmentation, attribution, etc.) in the cloud
• Combine and analyze large-scale data sources — including POS, retailer, Amazon Vendor Central, and syndicated data — to identify key performance drivers
• Collaborate closely with Market Insights, Category, and Sales teams to embed data science into commercial decision-making
• Automate and scale analytics using Python, SQL, and Snowflake to improve speed and consistency
• Partner with Data Foundations and Visualization teams to strengthen data pipelines and Power BI reporting
• Translate complex model results into clear business recommendations and present them to senior stakeholders

Here’s What You’ll Bring

• 4+ years of experience in Data Science or Advanced Analytics, ideally within consumer goods, retail, or e-commerce
• Proficiency building a variety of statistical and machine learning models (e.g. time series forecasting, linear/logistic regression, tree based and deep learning models)
• Proficiency in Python and/or R for machine learning (e.g. Scikit-learn, prophet, pyTorch etc.), SQL, and visualization tools (Power BI preferred)

Experience working with big data in the cloud (Snowflake, pySpark etc.) and/or experience deploying and monitoring machine learning models in production.

• Strong communication and problem-solving skills with the ability to translate technical insights into business outcomes
• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or other strongly quantitative field

What Success Looks Like

• Predictive models embedded into commercial planning and forecasting processes.
• Clear, actionable insights that improve revenue, margin, and decision speed.
• Scalable, automated analytics that reduce manual work and accelerate delivery.

Skills & Tools

Python | SQL | Snowflake | Power BI | Machine Learning | Predictive Modeling | Forecasting | Price Elasticity | Segmentation | Attribution | Data Pipelines | Data Automation | Retail & POS Data | Amazon Vendor Central | Consumer Insights

#LI-remote