Sr. Manager, Data Science

Sr. Manager, Data Science page is loaded## Sr. Manager, Data Science locations:
San Diego, CA, United Statestime type:
Full time posted on:
Posted Todayjob requisition :
JR 047454
** Let’s talk about the team:
** As a Data Science Manager, you will lead the organization’s data science and AI initiatives, collaborating with AI Product stakeholders and cross-functional teams to define and deliver impactful AI model solutions. You will drive the development roadmap, standardize experimentation, proactively mitigate AI-related risks, and ensure a seamless transition of models into production environments. As a strategic leader, you will engage stakeholders and optimize the use of data science to improve business outcomes and create value for patients and providers.

In this role, you will focus specifically on driving model development for AI products, creating measurable impact by strategically working with stakeholders to accelerate the launch of innovative AI products.
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* Location:

San Diego, CA
**** Let's talk about the role:
*** Stakeholder Engagement:
Build strong partnerships with AI Product stakeholders, Product Management, Engineering, and business teams to identify business challenges, opportunities, and define requirements for AI solutions.
* AI Model Development

Roadmap:

Lead and continually refine the AI model development roadmap, ensuring alignment between technical strategy, business goals, and emerging opportunities.
* Risk Mitigation:
Proactively identify and address AI-related risks, maintaining robust standards for model governance, compliance, and ethical deployment of AI solutions.
* Model Development Enablement:
Anticipate and overcome challenges in data science projects by bridging gaps in technology, data, platforms, or skillsets to ensure teams have the resources and support needed for timely product delivery.
* Standardization of Experimentation:
Establish and implement standardized processes for experimentation, including documentation, validation, and performance evaluation to ensure consistent, reproducible results.
* Technical Review and Guidance:
Participate in code and model reviews, providing technical guidance to ensure model robustness and quality while identifying areas for improvement.
* Collaboration with Engineering:
Partner with engineering teams to ensure smooth integration, scalability, and monitoring of AI models in production environments.
* Opportunity Analysis:
Help stakeholders pinpoint key problem areas where AI solutions can deliver measurable impact, leveraging organizational data and advanced analytics.
* Team Leadership and Development:
Mentor and empower a team of data scientists, fostering innovation and aligning technical skills with long-term AI strategy for impactful model delivery.
* Continuous Technical Strategization:
Monitor industry and academic breakthroughs in AI to proactively set and evolve the technical roadmap, ensuring the team is prepared to deliver state-of-the-art solutions.
** Let’s talk about you:
*** 8+ years of industry experience in Data Science, Machine Learning Engineering, or related fields.
* Master’s or PhD in Data Science, Machine Learning, Computer Science, Operations Research, Applied Statistics, Biomedical Informatics, or closely related disciplines.
* Proven experience managing and leading data science or AI teams, including mentoring junior members and developing team processes.
* Experience in productionization of AI models and collaboration with engineering for deployment and support.
* Excellent communication and stakeholder management skills.
* Proven ability to work across cross-functional teams and drive consensus on technical strategies and business priorities.
* Demonstrated expertise in model development, deployment, and performance evaluation for production-grade AI solutions.
* Strong foundation in probability, statistics, computer science, time series analysis, linear algebra, and discrete math.
* Extensive, practical experience applying advanced AI and machine learning methods—such as NLP, time-series analysis, computer vision, recommender systems, and reinforcement learning—using common algorithms, with a strong understanding…