Data Science Engineer V - US
At a glance
Mid-level Data Science role at Rackspace. Remote, United States · full-time · $165,830–$243,141 base.
dataroles summary, based on the employer's posting.
What you'll do
- Lead statistical, machine-learning and generative AI projects from design through delivery across multiple use cases
- Architect R-based analytical tools and Shiny applications that support several use cases
- Set technical standards through design reviews, and coach junior and mid-level data scientists
- Work with clinical experts to validate high-stakes models, assess AI safety and bias, and account for pediatric risks
- Help Research PIs plan studies and interpret results, while advising when compute-heavy work needs HPC resources
What you bring
- A STEM bachelor's degree or higher, or equivalent experience
- Six to nine years in data science, including ownership of significant projects
- Four to six years building and deploying ML or generative AI solutions, plus hands-on R, RStudio and Shiny experience
- At least one year informally mentoring data scientists
Who this fits
This remote US role suits a senior technical contributor who can set direction, own complex work and mentor other data scientists. You’ll partner with clinical leaders, business owners and Research PIs, and occasionally present technical work to groups of five to ten people.
From the employer
Summary: Owns complex, cross-cutting statistical/ML and generative AI initiatives that solve high-impact clinical and business problems, setting technical direction for the area, mentoring data scientists, and partnering directly with clinical and business leaders.
Required Education & Experience
- Bachelor's degree (or higher) in a STEM field, or equivalent experience.
- 6–9 years of experience in data science, with significant project ownership.
- 4–6 years hands-on building and productionizing ML/generative AI solutions.
- 4–6 years hands-on experience with R, RStudio, and Shiny application development, including production-grade interactive tools.
- 1+ year informally mentoring data scientists.
Preferred
- Deep experience with responsible-AI evaluation in a pediatric/clinical setting.
- Experience with fine-tuning or advanced RAG/agentic architectures.
- Experience running analyses in an HPC or research-computing environment for large-scale or computing intensive studies.
- Established working relationships with Research PIs, including study-design or analysis-planning input.
Knowledge, Skills, and Abilities
- Advanced expertise in statistics, ML, and data mining; independently designs model architectures and evaluation frameworks.
- Advanced expertise in R and RStudio; independently designs and architects production-grade Shiny applications.
- Deep understanding of generative AI/LLM architecture; independently designs RAG/agentic solutions for high-stakes clinical/operational use cases.
- Deep understanding of HPC/research-computing workflows; independently determines when compute-intensive work warrants HPC resources.
- Independently designs bias/safety evaluation frameworks, with rigorous scrutiny for pediatric populations.
- Mentors mid-level and junior data scientists on modeling, R/Shiny best practices, and responsible-AI practices.
- Occasionally presents technical work to cross-functional groups of 5–10 people.
Job Functions
- Architect and own end-to-end delivery of complex statistical/ML and generative AI initiatives spanning multiple use cases.
- Architect and own delivery of complex Shiny applications and R-based analytical tools spanning multiple use cases.
- Lead design reviews and set technical direction for own area; mentor junior/mid data scientists.
- Own human-in-the-loop validation processes for high-stakes models within own domain, partnering with clinical SMEs.
- Own bias/safety/explainability evaluation for owned AI outputs, with particular attention to pediatric-population risk.
- Partner directly with Research PIs on study design, analysis planning, and interpretation of complex results.
- Advise on appropriate use of HPC/research-computing resources for compute-intensive modeling work.
- Build tools/libraries that scale data science products across multiple teams.
- Partner directly with clinicians and business owners to define and prioritize high-impact problems.
About Rackspace Technology
Rackspace Technology is the trusted operator of the full enterprise AI stack, from governed private cloud to AI inference and agents in production. From edge to core to cloud, we operate the infrastructure, data layer, and software integration to deliver business outcomes with the predictable cost, reliability, security, and compliance that regulated and mission-critical environments demand. We support customers in more than 120 countries with AI capabilities spanning private cloud, public cloud, applications, data and cyber resilience.
More on Rackspace Technology
Though we’re all different, Rackers thrive through our connection to a central goal: to be a valued member of a winning team on an inspiring mission. We bring our whole selves to work every day. And we embrace the notion that unique perspectives fuel innovation and enable us to best serve our customers and communities around the globe. We welcome you to apply today and want you to know that we are committed to offering equal employment opportunity without regard to age, color, disability, gender reassignment or identity or expression, genetic information, marital or civil partner status, pregnancy or maternity status, military or veteran status, nationality, ethnic or national origin, race, religion or belief, sexual orientation, or any legally protected characteristic. If you have a disability or special need that requires accommodation, please let us know.
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