Product Manager Gen AIAIData Science
Product Manager Gen AIAIData Science
Posted on :
22-01-2025
Employer Active
1 Vacancy
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Monthly Salary
Not Disclosed
Salary Not Disclosed
Vacancy
1 Vacancy
Posted on :
22-01-2025
Job Description
An experienced Senior Product Manager to lead the vision strategy and execution of AI and Data Science products. As a senior leader you
will be instrumental in driving product innovation aligning crossfunctional teams and delivering marketleading AIpowered solutions. Your leadership and strategic insight will help shape
the future of our AI offerings and ensure success across the product portfolio.
will be instrumental in driving product innovation aligning crossfunctional teams and delivering marketleading AIpowered solutions. Your leadership and strategic insight will help shape
the future of our AI offerings and ensure success across the product portfolio.
1. Product Vision & Strategy:
Define Product Strategy: Lead the strategic direction for Generative AI and
Data Science products ensuring alignment with business goals and market
trends.
AI/ML Product Roadmap: Develop prioritize and manage the product
roadmap incorporating customer feedback emerging technologies and
business objectives.
Define Product Strategy: Lead the strategic direction for Generative AI and
Data Science products ensuring alignment with business goals and market
trends.
AI/ML Product Roadmap: Develop prioritize and manage the product
roadmap incorporating customer feedback emerging technologies and
business objectives.
Innovation & Differentiation: Drive product innovation through continuous
research into the latest trends in AI machine learning and data science
ensuring competitive differentiation in the market.
2. AI/ML & Generative AI Product Development:
Product Requirements: Translate complex AI and Data Science concepts into
clear actionable product requirements and user stories that engineering and
data science teams can execute.
Model Integration & Deployment: Collaborate with data scientists and ML
engineers to ensure the seamless integration of AI/ML models and generative AI
technologies into product features.
Scalability & Reliability: Ensure AI/ML models and products are scalable
reliable and optimized for performance across different platforms and
environments.
3. CrossFunctional Collaboration:
Collaborate Across Teams: Work closely with engineering design marketing
sales and customer success teams to deliver AIpowered products on time and
within scope.
Executive Reporting: Communicate product progress opportunities and risks
to senior leadership ensuring alignment with strategic priorities.
Customer Engagement: Engage with customers to understand their needs
gather feedback and ensure the development of products that solve realworld
problems.
4. GotoMarket Strategy & Product Launch:
Product Launches: Plan and execute product launches working with
marketing and sales teams to ensure successful gotomarket strategies.
Positioning & Messaging: Collaborate with marketing to define positioning
messaging and competitive differentiation for AI/ML products.
Customer Onboarding: Drive customer adoption of AI/ML products
collaborating with customer success and sales teams to ensure customers
achieve value quickly.
5. Market Research & Competitive Analysis:
Industry Insights: Continuously monitor market trends competitive products
and emerging technologies in Generative AI AI and Data Science to inform
product strategy.
Customer Use Cases: Identify and prioritize key use cases for Generative AI
and Data Science applications across various industries ensuring products
research into the latest trends in AI machine learning and data science
ensuring competitive differentiation in the market.
2. AI/ML & Generative AI Product Development:
Product Requirements: Translate complex AI and Data Science concepts into
clear actionable product requirements and user stories that engineering and
data science teams can execute.
Model Integration & Deployment: Collaborate with data scientists and ML
engineers to ensure the seamless integration of AI/ML models and generative AI
technologies into product features.
Scalability & Reliability: Ensure AI/ML models and products are scalable
reliable and optimized for performance across different platforms and
environments.
3. CrossFunctional Collaboration:
Collaborate Across Teams: Work closely with engineering design marketing
sales and customer success teams to deliver AIpowered products on time and
within scope.
Executive Reporting: Communicate product progress opportunities and risks
to senior leadership ensuring alignment with strategic priorities.
Customer Engagement: Engage with customers to understand their needs
gather feedback and ensure the development of products that solve realworld
problems.
4. GotoMarket Strategy & Product Launch:
Product Launches: Plan and execute product launches working with
marketing and sales teams to ensure successful gotomarket strategies.
Positioning & Messaging: Collaborate with marketing to define positioning
messaging and competitive differentiation for AI/ML products.
Customer Onboarding: Drive customer adoption of AI/ML products
collaborating with customer success and sales teams to ensure customers
achieve value quickly.
5. Market Research & Competitive Analysis:
Industry Insights: Continuously monitor market trends competitive products
and emerging technologies in Generative AI AI and Data Science to inform
product strategy.
Customer Use Cases: Identify and prioritize key use cases for Generative AI
and Data Science applications across various industries ensuring products
deliver maximum impact.
Partnerships: Identify potential partnerships with technology vendors and
service providers that can enhance the product offering.
6. DataDriven Product Management:
DataDriven Decisions: Use data to drive decisionmaking product
prioritization and feature development ensuring a clear focus on customer
value and business outcomes.
Define Success Metrics: Establish clear product KPIs and OKRs to measure
product success such as customer satisfaction revenue growth and AI model
performance.
A/B Testing & Experimentation: Implement A/B testing and other experimental
methods to optimize AI/ML features and product performance.
7. Leadership & Mentorship:
Mentor & Lead: Provide mentorship to junior product managers and cross
functional team members fostering a collaborative and innovative product
culture.
CrossTeam Leadership: Lead crossfunctional teams through the entire
product lifecycle from ideation to delivery ensuring seamless collaboration
across teams.
8. Ethics Privacy & AI Compliance:
Ethical AI Practices: Ensure that AI and machine learning models adhere to
ethical guidelines promoting fairness transparency and accountability.
Data Privacy Compliance: Ensure products are developed in accordance with data
privacy regulations (GDPR CCPA) and internal policies
Partnerships: Identify potential partnerships with technology vendors and
service providers that can enhance the product offering.
6. DataDriven Product Management:
DataDriven Decisions: Use data to drive decisionmaking product
prioritization and feature development ensuring a clear focus on customer
value and business outcomes.
Define Success Metrics: Establish clear product KPIs and OKRs to measure
product success such as customer satisfaction revenue growth and AI model
performance.
A/B Testing & Experimentation: Implement A/B testing and other experimental
methods to optimize AI/ML features and product performance.
7. Leadership & Mentorship:
Mentor & Lead: Provide mentorship to junior product managers and cross
functional team members fostering a collaborative and innovative product
culture.
CrossTeam Leadership: Lead crossfunctional teams through the entire
product lifecycle from ideation to delivery ensuring seamless collaboration
across teams.
8. Ethics Privacy & AI Compliance:
Ethical AI Practices: Ensure that AI and machine learning models adhere to
ethical guidelines promoting fairness transparency and accountability.
Data Privacy Compliance: Ensure products are developed in accordance with data
privacy regulations (GDPR CCPA) and internal policies
Employment Type
Full Time
Key Skills
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