Technical Product Manager, TrueAccord

• Bachelor's degree or equivalent professional experience in Computer Science, Engineering, Statistics, Mathematics, or a related technical field
• 3+ years of experience in technical product management, preferably working with data science, machine learning, or AI-powered products
• Proven ability to define product strategy, develop roadmaps, and manage a product backlog
• Strong understanding of the data science lifecycle, including data collection, cleaning, modeling, validation, and deployment
• Familiarity with common machine learning algorithms, statistical concepts, and data analysis techniques
• Experience working closely with engineering and data science teams in an Agile/Scrum environment
• Excellent analytical and problem-solving skills, with a data-driven approach to decision-making
• Exceptional communication, presentation, and interpersonal skills, with the ability to influence and collaborate effectively across teams and levels
• Demonstrated ability to translate complex technical concepts into clear business value

Desirable

• We are seeking an experienced and visionary Technical Product Manager (TPM) to lead the product strategy and execution for our Data Science team
• This is a pivotal opportunity to shape the future of AI and Data Science at TrueML
• This critical role sits at the intersection of data science, engineering, and business strategy. You will be responsible for defining, prioritizing, and delivering innovative data-driven products and capabilities that leverage machine learning, statistical modeling, and advanced analytics to solve key business challenges and unlock new opportunities
• As the product leader for our data science initiatives, you will work closely with data scientists, engineers, business stakeholders, and customers to translate complex technical concepts and user needs into a compelling product roadmap and tangible results
• Product Strategy & Vision: Define and champion the product vision, strategy, and roadmap for data science initiatives, aligning with overall company objectives and market opportunities
• Roadmap & Prioritization: Develop and maintain a prioritized product backlog based on business value, technical feasibility, user feedback, and strategic goals. Make the tough trade-off decisions necessary to ensure we efficiently deliver value to users and our business
• Requirements Definition: Collaborate closely with data scientists, engineers, designers, and stakeholders to gather requirements, define use cases, and translate them into clear, detailed technical specifications and user stories
• Cross-functional Collaboration: Act as the primary liaison between the Data Science team and other departments (Engineering, Marketing, Sales, Operations, etc.) to ensure alignment and successful product development and launch
• Technical Understanding: Develop a deep understanding of our data infrastructure, machine learning models, algorithms, and analytical techniques to effectively guide product development and communicate technical concepts to non-technical audiences
• Product Lifecycle Management: Oversee the entire product lifecycle from ideation and discovery through development, launch, iteration, and end-of-life
• Market & User Research: Conduct market research, competitive analysis, and user research to identify unmet needs, validate hypotheses, and inform product decisions
• Go-to-Market: Partner with marketing and sales teams to define go-to-market strategies, positioning, and messaging for new data products and features
• Performance Monitoring: Define key performance indicators (KPIs) and success metrics for data science products; monitor performance, analyze results, and drive continuous improvement
• Stakeholder Management: Communicate product plans, progress, and insights effectively to stakeholders at all levels, including executive leadership