POSITION SUMMARY: The Data Scientist II independently delivers AI, analytical and data science solutions to complex business problems. The incumbent builds on foundational AI, data science skills and applies deep modeling, diagnostic, and problem-solving capabilities to develop, evaluate, and refine analytical solutions that inform business decisions. The Data Scientist II balances AI and analytical rigor, speed of execution, and solution scalability, while working closely with business partners, senior data scientists, and analytics engineers to ensure solutions are fit for purpose and deliver measurable value.

PRINCIPAL RESPONSIBILITIES:

• Develops, evaluates, and refines statistical, machine learning, and AI models using appropriate performance metrics and diagnostics.

• Supports model and solution monitoring and diagnostics, resolving common modeling issues (e.g., transformations, data limitations, bias, drift, hallucination detection, embeddings, vector search, semantic retrieval, or model assumptions).

• Enhances and scales existing models or analytics solutions to improve performance, maintainability, or business usability.

• Performs hypothesis testing, prompt engineering, time series analysis, and experimentation measurement to assess impact and support data-driven recommendations.

• Works directly with business stakeholders to: clarify requirements, scope analytical approaches, and ensure outputs align with operational and commercial context.

• Translates analytical findings into clear insights that directly answer business questions and inform decisions.

• Interprets common operational, financial, and performance metrics and applies appropriate analytic techniques to uncover insights.

• Clearly communicates analytical results and recommendations to technical and non-technical audiences.

• Partners with analytics engineering and platform teams to ensure analytical solutions integrate appropriately with downstream systems.

• Documents solution design, assumptions, data definitions, and limitations thoroughly to support reuse and transparency.

• Performs other job-related duties as assigned or apparent.

QUALIFICATIONS:

• Strong proficiency in Python for data analysis, modeling, AI, and solution development.

• Strong working knowledge of SQL and relational data concepts.

• Solid understanding of Generative AI, large language models (LLMs), and common enterprise use cases.

• Ability to write well-functionalized, readable code and collaborate using version control (Git).

• Experience working with cloud-based data platforms and infrastructure, such as Snowflake and AWS, to support analytics, GenAI and data science workflows.

• Experience with common commercial analytics topics (e.g. pricing optimization, customer segmentation, customer churn/lifetime value, etc.), operational analytics topics (e.g. logistics analytics, route optimization, maintenance optimization, etc.) or Customer Experience analytics topics (e.g. Average handle time, containment rate, deflection rate, NPS, customer sentiment, etc).

• Familiarity with AI-based coding assistants like GitHub CoPilot, Cursor, Claude Code.

• Knowledge of Excel and PowerBI.

• Master's Degree in an analytical field (Mathematics, Computer Science, Information Management, Statistics, Engineering) - preferred.

MINIMUM REQUIREMENTS:

• Bachelor's Degree in an analytical field (Mathematics, Computer Science, Information Management, Statistics, Engineering).

• 3+ years of demonstrated experience working with large databases to perform complex analysis.

• 3+ years of experience with advanced statistical modeling, machine learning methods, and/or AI models.

• 3 years of experience with advanced programming in Python and SQL, conducting complex statistical analysis and building machine learning algorithms or AI applications with large databases in cloud computing environments.

*This position is in-office in Phoenix, AZ and requires residing in Phoenix.

* Required Skills: Advanced programming in Python and SQL, conducting complex statistical analysis and building machine learning algorithms or AI applications with large databases in cloud computing environments.

Rewarding Compensation and Benefits

Eligible employees can elect to participate in:
• Comprehensive medical benefits coverage, dental plans and vision coverage.
• Health care and dependent care spending accounts. 
• Short- and long-term disability.
• Life insurance and accidental death & dismemberment insurance.
• Employee and Family Assistance Program (EAP).
• Employee discount programs.
• Retirement plan with a generous company match.
• Employee Stock Purchase Plan (ESPP).

• Paid Time Off (PTO)

• Benefits:

The statements used herein are intended to describe the general nature and level of the work being performed by an employee in this position, and are not intended to be construed as an exhaustive list of responsibilities, duties and skills required by an incumbent so classified.  Furthermore, they do not establish a contract for employment and are subject to change at the discretion of the Company.