Sr Data Scientist I

Waystar • Lehi, UT

23h

About The Position

Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers. Incumbents whose primary role is technical and focused on data storage, warehousing and systems architecture should be matched to Database Engineering or Storage Engineering. Incumbents whose focus is the quantitative analysis of complex business problems and issues using data from internal and external sources to provide insight to decision-makers should be matched to Business Intelligence. Incumbents whose primary role is technical and focused on designing and building system-generated reports, reporting tools and dashboards for data generation should be matched to Data Informatics. Incumbents whose focus is primarily on experimental design and advanced or complex statistical analysis and modeling of datasets should be matched to Statistician/Mathematician. This is a product engineering role in which employees work with multiple types of business data. Incumbents whose focus is primarily on analysis and modeling of financial, marketing or pricing data should be matched to Finance, Market Research or Pricing as appropriate. May be internal operations-focused or external client-focused, working in conjunction with Professional Services and outsourcing functions.

Requirements

• Master's or Ph.D. in a quantitative field such as Computer Science, Statistics, Mathematics, Physics, Engineering, or a related discipline.
• 4-7+ years of hands-on experience in a data science role, with a strong track record of developing and deploying machine learning models.
• Proficiency in Python (e.g., scikit-learn, TensorFlow, PyTorch, pandas, numpy) and SQL is essential.
• Demonstrated experience with big data technologies (e.g., Spark, Hadoop, AWS EMR, GCP Dataflow).
• Strong understanding of statistical modeling, machine learning algorithms, and experimental design (A/B testing).
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn).
• Excellent problem-solving skills and the ability to work independently and collaboratively in a fast-paced environment.
• Strong communication and presentation skills, with the ability to explain complex technical concepts to diverse audiences.

Nice To Haves

• Experience with cloud platforms (AWS, GCP, or Azure) and MLOps practices is a plus.

Responsibilities

• Design, develop, and implement machine learning models and algorithms to solve complex business problems, including predictive modeling, recommendation systems, segmentation, and anomaly detection.
• Conduct in-depth exploratory data analysis to identify trends, patterns, and insights from large, diverse datasets.
• Translate business problems into well-defined data science projects, including defining objectives, metrics, and success criteria.
• Collaborate with engineering teams to deploy and maintain data science solutions in production environments, ensuring scalability and reliability.
• Communicate complex analytical findings and recommendations clearly and concisely to technical and non-technical stakeholders through presentations, reports, and dashboards.
• Develop and maintain robust data pipelines and perform data cleaning, transformation, and feature engineering to prepare data for model building.
• Evaluate and monitor the performance of deployed models, iterating and refining them to ensure optimal results.
• Stay up-to-date with the latest advancements in data science, machine learning, and artificial intelligence, and proactively propose new technologies and methodologies.
• Mentor junior data scientists and contribute to a culture of continuous learning and knowledge sharing within the team.

Benefits

• Competitive total rewards (base salary + bonus, if applicable)
• Customizable benefits package (3 medical plans with Health Saving Account company match)
• We offer generous paid time off for our non-exempt team members, starting with 3 weeks + 13 paid holidays, including 2 personal floating holidays.
• We also offer flexible time off for our exempt team members + 13 paid holidays
• Paid parental leave (including maternity + paternity leave)
• Education assistance opportunities and free LinkedIn Learning access
• Free mental health and family planning programs, including adoption assistance and fertility support
• 401(K) program with company match
• Pet insurance
• Employee resource groups

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level