Data Scientist

Wahl Empowers People To Be Their Best!

Help Shape the Future of Decision-Making at Wahl

At Wahl, data isn't just numbers- it's the story behind how we innovate, build, plan, and deliver products people depend on every single day. As a Data Scientist, you'll turn raw information into clear, compelling insights that help our teams make smarter decisions faster. If you thrive where statistical rigor meets creative problem‑solving, and you love transforming chaos into clarity, this role gives you the opportunity to influence strategies across the entire organization.

What You'll Do

As a Data Scientist, you'll explore complex datasets, build predictive models, and surface insights that drive real business value. Your day-to-day will include:

• Develop predictive and descriptive models (regression, classification, clustering, forecasting, etc.) to solve business problems.
• Explore, clean, and transform data from Snowflake, relational SQL databases, flat files, APIs, and Excel sources.
• Design and optimize analytical datasets within Snowflake for modeling and reporting.
• Write efficient SQL to extract, join, and aggregate large datasets.
• Build reusable data science pipelines and feature engineering processes.
• Validate, test, and monitor models for accuracy, bias, and performance.
• Partner with business stakeholders to understand requirements and define success metrics.
• Translate analytical findings into clear business insights and recommendations.
• Publish results through Power BI dashboards, semantic models, or other data products.
• Collaborate with data engineers and BI developers to produce models.
• Document methodologies, assumptions, and model behavior.

What You'll Bring

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or related field.
• 5+ years of experience in data science, analytics, or applied statistics.
• Strong SQL skills and experience working with cloud data warehouses (Snowflake preferred).
• Proficiency in Python or R for data analysis and modeling.
• Experience with Power BI or similar BI tools (Tableau, Looker, etc.)
• Solid understanding of statistical methods and machine learning algorithms.
• Experience working with messy, real-world datasets from multiple sources.
• Ability to understand business needs, translate them into effective solutions, and communicate technical concepts to a non-technical audience.

Technical Skills

• Snowflake
• SQL (T‑SQL, PostgreSQL, MySQL, etc.)
• Python or R
• Power BI
• Advanced Excel (formulas, Power Query)
• Pandas, NumPy, scikit‑learn (or equivalent libraries)
• Jupyter / Notebooks
• Git

Desired Experience

• Experience deploying models into production environments.
• Familiarity with feature stores, model versioning, and MLOps concepts.
• Knowledge of dimensional modeling and data warehouse design.
• Experience with time-series forecasting and experimentation (A/B testing).
• Background in retail, manufacturing, supply chain, e-commerce, or operations analytics.
• Experience using Git and CI/CD pipelines.

Core Competencies

• Action Oriented
• Collaboration
• Optimizes Work Processes
• Nimble Learning
• Demonstrates self-awareness
• Values Differences

Why You'll Love Wahl Clipper

We offer a competitive benefits package designed to support your well-being and growth, including:

• Low-cost BCBSIL medical, dental, and vision plans
• A generous company-matched 401(k) and profit sharing
• Tuition support to fuel your learning
• Paid holidays and a vibrant, casual work environment

But that's just the beginning. At Wahl, you'll also enjoy:

• A legacy of quality and innovation.
• A team that values your expertise and ideas.
• Opportunities to grow and contribute to meaningful projects.
• A culture built on respect, precision, and progress.

Ready to Build What's Next?

If you're a data professional who blends analytical rigor with creative thinking- and you're excited to shape the insights that shape our future, we'd love to meet you. Apply today and help power the next chapter of Wahl's innovation.

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