Staff Data Scientist

POSITION DESCRIPTION

JOIN OUR TEAM

At VASA Fitness, we want to create an uplifting experience for everyone by offering inclusive, accessible, and on-trend fitness. The foundation of our brand is rooted in a culture centered on unity, passion, love, integrity, fun, and trust. Because our culture is alive--embodied by members and team members alike--VASA is a place where lives are changed because of authentic connections made within our supportive community.

BENEFITS

All employees receive two complimentary gym memberships--one for themselves and another to give away--plus 401k options. Additional benefit packages are available for employees who work 30+ hours per week.

• Salaried Employees: Flexible Vacation Plan, Paid Holidays, Paid Parental Leave, and Health, Dental, Vision Benefits

Come join VASA Fitness and join a passionate, fun, and united team!

Proud to be a 'Great Place to Work' certified company!

PURPOSE

The Staff Data Scientist serves as a senior technical leader responsible for the design, development, and operational reliability of data science and machine learning systems supporting VASA Fitness digital products, member analytics, and operational decision-making. This role provides technical leadership across complex data initiatives, establishes data science standards and best practices, and partners with cross-functional teams to deliver scalable, trustworthy, and production-grade models and analytics.

The Staff Data Scientist contributes to data and analytics strategy, model architecture, experimentation practices, and process improvement while mentoring data scientists and analysts and influencing technical direction across the organization.

• Lead the design, development, deployment, and support of machine learning models, statistical analyses, and data science systems in production.
• Provide technical leadership across complex, cross-functional data science and analytics initiatives and platform modernization efforts.
• Design and support scalable data pipelines, feature stores, model serving, and cloud-native ML infrastructure.
• Establish and promote data science standards, modeling patterns, experimentation practices, and operational procedures for models in production.
• Lead model design reviews, code reviews, and methodology discussions across data science and engineering teams.
• Partner with engineering leadership, product teams, and business stakeholders to translate business problems into data science solutions, priorities, and implementation strategies.
• Support model reliability, monitoring, drift detection, scalability, and operational performance across critical production systems.
• Contribute to cloud data architecture, MLOps strategy, CI/CD practices, and model delivery automation.
• Mentor and support data scientists and analysts through technical guidance, collaboration, and knowledge sharing.
• Drive continuous improvement initiatives related to data science processes, model quality, validation, automation, and operational excellence.
• Evaluate and implement emerging techniques, tools, and practices across machine learning, statistical modeling, and AI-assisted development and automation.
• Participate in operational support, incident response, root cause analysis, and technical troubleshooting for data and model issues as required.

QUALIFICATIONS

• 10+ years of professional data science and machine learning work, with a real track record at staff, principal, or equivalent level. We care about scope of impact, not titles on a resume.
• Demonstrated shipping velocity. Tell us specifically what models or analyses you have built and shipped in the last 12 months and what decisions they drive in production today.
• Deep work in Python and SQL, with fluency in the modern ML/data stack (e.g. pandas, scikit-learn, PyTorch or TensorFlow, Spark/Databricks). We choose the right tool per problem and expect Staff data scientists to lead that choice.
• Strong cloud and data platform experience -- AWS (S3, SageMaker, Lambda, IAM) and a lakehouse such as Databricks. You have built data and ML systems end-to-end and operated them under real load.
• Concrete work with modern AI tooling you can talk through in depth -- LLM-backed pipelines you built, models you put into production, evals and validation you wrote, automations that changed how a team operates. "I use ChatGPT for EDA" is not the bar.
• Experience owning models and data products through their full lifecycle -- framing, build, validation, deployment, monitoring, retraining, retirement.
• Strong statistical and experimentation instincts: causal inference, A/B testing, feature and data leakage, drift, class imbalance, and the operational consequences of each.
• Communication that lands. You can write an analysis stakeholders actually read, run a model review without making people defensive, and explain trade-offs and uncertainty to a non-technical executive.
• Bonus: prior staff-level work at a lean, AI-forward team; consumer-scale membership, subscription, or retention modeling experience; or building data/ML tooling around LLMs.

WORKING CONDITIONS

Primary work in a fitness facility and office setting. Temperature variations can occur. The environment includes some ambient noise such as talking and use of gym equipment and machinery.

PHYSICAL AND MENTAL ACTIVITIES AND REQUIREMENTS

• Talking: Especially where one must frequently convey detailed or important instructions or ideas accurately, loudly, or quickly.
• Physical Strength: Sitting, standing, and walking. Must be able to lift, push, pull, and move a minimum of 30 pounds.
• Reasoning Ability: Ability to deal with a variety of variables under limited standardization. Able to interpret various instructions and relay instructions to clients.
• Attendance is an essential duty of the position. Employees must work regularly scheduled shifts, during business hours to assist members and sell services in-person.

This position description intends to describe the general nature and level of work being performed by people assigned to this job. It is not intended to include all duties and responsibilities. The order in which duties and responsibilities are listed is not significant.

VASA Fitness is an Equal Opportunity Employer