Data Scientist 3-USD

Mindlance

San Diego, CA

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JOB DETAILS

SALARY

$66–$77.44 Per Hour

SKILLS

AWS Lambda, Amazon Web Services (AWS), Analysis Skills, Application Programming Interface (API), Artificial Intelligence (AI), Business Skills, Career Development, Cloud Computing, Communication Skills, Computer Workstations, Cross-Functional, Data Analysis, Data Processing, Data Science, Data Sets, Documentation, Documentation Models, Identify Issues, Injections, Machine Learning, Model Validation, Modeling Languages, Needs Assessment, Performance Metrics, Presentation/Verbal Skills, Problem Solving Skills, Python Programming/Scripting Language, Quality Metrics, Regulatory Compliance, SQL (Structured Query Language), Team Player, Warehousing, Willing to Travel, Writing Skills

LOCATION

San Diego, CA

POSTED

4 days ago

Meet the team:
As part of the Commercial Data Science & AI/ML team, you will join a team responsible for leveraging data, analytics, and artificial intelligence to drive commercial growth and data-related innovation within the company. As a Senior Data Scientist, you will build and deliver AI solutions spanning generative AI and traditional machine learning, with a primary focus on automated generation pipelines and LLM-powered applications using Python and Amazon Bedrock, alongside contributions to the team’s production ML models. This role will contribute to cross-functional projects that enhance operational efficiency, unlock self-service analytics, and accelerate data-driven decision-making through advanced AI. The ideal candidate will bring hands-on generative AI experience, strong Python and cloud development skills, and the drive to ship production solutions that create measurable business value.
Where you come in:
· Build and deploy generative AI solutions using Amazon Bedrock and Python, delivering automated generation pipelines that transform data into actionable business outputs.
· Engineer and refine prompts and generation workflows that produce accurate, consistent results, reducing manual analysis cycles and accelerating time-to-insight for commercial and analytics teams.
· Develop evaluation frameworks for generative AI outputs, measuring quality, accuracy, and relevance to ensure production pipelines meet business standards before deployment.
· Contribute to the architecture of AI-powered applications that connect large language model capabilities with the team’s data platform, enabling intelligent, context-aware solutions for cross-functional partners.
· Train and validate ML models (classification, regression, clustering) using Python and established team frameworks, with clear documentation of methodology and performance metrics.
· Develop and maintain Lambda functions and data processing workflows that support AI and analytics pipelines across the team’s AWS-native cloud stack.
· Apply responsible AI practices to generative AI solutions — output safety checks, prompt injection safeguards, and documentation of model behavior — ensuring production pipelines meet the team’s quality and compliance standards.
· Present analysis findings and demonstrate AI capabilities to immediate stakeholders, translating model outputs and generative AI results into clear recommendations with supporting visuals.
What makes you successful:
· GenAI: Hands-on experience building applications with large language model APIs (e.g., Amazon Bedrock) including prompt engineering, output evaluation, and generation pipeline development.
· Python/Cloud: Strong Python development skills with practical experience building and deploying applications on AWS services (Lambda, S3, Redshift).
· Modeling: Hands-on experience applying supervised and unsupervised ML techniques to real-world business problems, with documented performance outcomes.
· Data: Proficiency in SQL for data manipulation and analysis, with experience working with large-scale datasets in a warehouse environment.
· Problem-solving: Demonstrated ability to identify business problems suited for AI/ML solutions and deliver practical, production-ready implementations.
· Communication: Clear written and verbal communication skills with the ability to explain technical findings — including generative AI capabilities and limitations — to non-technical stakeholders.
· Collaboration: Openness to feedback, a habit of documenting technical decisions, and comfort working closely with senior team members on shared projects.
What you’ll get:
A front row seat to life changing CGM technology.
A full and comprehensive benefits program.
Growth opportunities on a global scale.
Access to career development through learning programs.
An innovative, industry leading organization committed to our employees, customers, and communities.
Travel Required:
5-15%
Experience and Education Requirements: (this section should not be modified)
Mapped to the Global Career Framework level and title.
Please Note: This data is pulled in automatically based on the job code when creating requisition in SuccessFactors.

Remote Workplace: Your location will be a home office; you are not required to live within commuting distance of your assigned Client site (typically 75 miles/120km). If you reside within commuting distance of a Client site (typically 75 miles/120km) a hybrid working environment may be available. Ask about our Flex workplace option.
Flex Workplace: Your primary location will be a home office. You will not have an assigned workstation and will work with your manager to determine office visit needs. You must live within commuting distance of your assigned Client site (typically 75 miles/120km).

EEO:
“Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”

Data Scientist 3-USD

Mindlance

San Diego, CA

About the Company

Mindlance

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