Data Scientist

Piper Companies is seeking a Data Scientist to join a growing team supporting high‑impact data initiatives. The Data Scientist will play a critical role in transforming complex datasets into actionable insights, driving operational efficiency, and enabling data‑driven decision‑making across the organization. This is an opportunity to influence large‑scale analytic programs, build advanced machine learning models, and contribute to meaningful, mission‑focused outcomes.

Responsibilities

The Data Scientist will make an impact by:

• Performing advanced scientific work involving analytical, statistical, and programming skills to collect, analyze, and interpret large datasets.
• Using large datasets to identify opportunities for product and process optimization.
• Designing and implementing predictive models to drive improved customer experience, operational efficiency, and business outcomes.
• Mining, analyzing, and interpreting data using a variety of statistical and data tools.
• Building and deploying machine learning models, algorithms, and simulations.
• Developing processes and ML-based tools to monitor, validate, and optimize model performance and data accuracy.
• Evaluating new data sources, data pipelines, and data collection methodologies for effectiveness and accuracy.
• Delivering data-driven insights to support strategic business decisions.
• Communicating analytical findings to non-technical stakeholders through presentations and written reports.
• Troubleshooting analytic challenges and working independently to resolve complex problems.
• Supporting requirement gathering for analytic deliverables and solutions.
• Providing hands-on expertise in data science, predictive analytics, machine learning, and artificial intelligence.

Required Qualifications

• Bachelor’s degree in Data Science or a related quantitative field.
• 5+ years of professional experience in data science, analytics, or machine learning roles.
• Strong understanding of logistic regression, statistical theory, and generalized estimating equations (GEE).
• Proven experience developing machine learning models and engineering features using:
  • Python, R, SQL, PySpark
  • Databricks
  • Machine learning with regularization techniques (including LASSO)
  • Amazon SageMaker AI/ML tools
• Ability to create complex SQL queries for testing and analytical workflows.
• Experience designing ML pipelines and working with MLOps frameworks.
• Hands-on experience with model tuning, model governance, and performance optimization.
• Familiarity with the following tools: MLflow, GitHub, Docker.
• Ability to work with engineering teams to source appropriate data and assess system/model performance.
• Strong problem-solving mindset and ability to work independently.

Preferred Qualifications

• Experience in healthcare or claims data analytics.
• Statistics background with knowledge of queuing theory.
• Experience with SAS for advanced statistical analysis.

Soft Skills

• Strong written and verbal communication skills; able to present technical concepts to non‑technical audiences.
• Independent self‑starter with a proactive approach to challenges.
• Ability to collaborate with cross-functional teams including engineering, analytics, and program stakeholders.

Keywords: #LI-CG1 #REMOTE

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