Senior Data Science Engineer: Generative AI & Shiny Lead

Rackspace Technology, Inc.; United States; Remote; USD 166,000 - 243,000; Full time

Job summary

Rackspace Technology is seeking a senior data science leader to drive cross‑cutting ML and generative AI initiatives. You will mentor data scientists, partner with clinical and business leaders, and own end‑to‑end model development, validation, and deployment.

You’ll architect Shiny apps and R‑based analytical tools, guide research design, and ensure responsible‑AI practices in high‑stakes settings, including pediatric contexts.

Qualifications

• Bachelor's degree or higher in a STEM field, or equivalent experience.
• 6–9 years of data science with project ownership.
• 4–6 years building and productionizing ML/generative AI solutions.
• 4–6 years hands‑on experience with R, RStudio, and Shiny, incl. production‑grade tools.
• 1+ year mentoring data scientists.

Responsibilities

• Architect and own end‑to‑end delivery of complex statistical/ML and generative AI initiatives.
• Architect and own delivery of complex Shiny applications and R‑based tools.
• Lead design reviews and set technical direction for own area; mentor junior/mid data scientists.
• Own human‑in‑the‑loop validation for high‑stakes models with clinical SMEs.
• Own bias/safety/e explainability evaluation for AI outputs, esp. pediatric populations.
• Partner with Research PIs on study design, analysis planning, and interpretation.

Skills

Statistics/ML/Data mining

Mentoring data scientists

Cross-functional collaboration

Education

Bachelor's degree in STEM or equivalent

Tools

R

RStudio

Shiny

Job description

Rackspace Technology is seeking a senior data science leader to drive cross‑cutting ML and generative AI initiatives. You will mentor data scientists, partner with clinical and business leaders, and own end‑to‑end model development, validation, and deployment.

You’ll architect Shiny apps and R‑based analytical tools, guide research design, and ensure responsible‑AI practices in high‑stakes settings, including pediatric contexts.