• The ideal candidate will possess a technical background in machine learning technologies, proven product leadership experience, and a passion for data-driven product innovation
• Bachelor’s or Master’s degree or equivalent experience in Computer Science, Mathematics, Physics, or an equivalent. Sophisticated knowledge of Machine Learning, Analytics or Data Science preferred
• Minimum of 8+ years in product management, with at least 3 years in a leadership role directly overseeing teams that specialize in machine learning or recommendations systems. Demonstrated experience in successfully launching and managing products is essential
• Current knowledge of machine learning, artificial intelligence, and data analytics platforms. Experience with modern recommendation algorithms, personalization techniques, and predictive modeling is required
• Proven track record to lead, inspire, and grow teams in a fast-paced environment. Should possess strong mentoring and coaching skills to foster talent within the team
• Strong skills in analytics with the ability to think strategically and translate strategies into actionable plans. Capable of making tough decisions and solving sophisticated problems under pressure
• Exceptional interpersonal and communication skills, with the ability to articulate ideas to both technical and non-technical audiences. Be comfortable presenting to team members and external partners
• A deep understanding of user experience, with a track record of developing user-focused products that improve engagement
• Dynamic, resourceful, and able to thrive in a changing environment while maintaining focus on key business goals and personal objectives

Desirable

• We are seeking a product leader to own the strategy and execution for our core recommendations team
• In this pivotal role, you will relentlessly improve our recommendations system that delivers results for our members by harnessing the power of machine learning, next-gen AI, LLMs, user behavior modeling, and personalization!
• You will report directly to the SVP of Core Products
• Develop and implement a product strategy that brings to bear machine learning and recommendation technologies to deliver personalized and impactful user experiences. Align this strategy with broader business goals to ensure coherence and support from top management
• Actively lead and scale a team of hard-working product managers. Foster a culture of innovation, accountability, and continuous improvement. Provide mentorship and career development opportunities to team members, ensuring they are motivated and equipped to meet their goals
• Work closely with engineering leaders, data science, and other department heads to synchronize efforts and prioritize projects that improve product impact and value. Facilitate seamless communication between teams to avoid silos and ensure everyone is aligned with the product direction
• Promote the integration of sophisticated machine learning capabilities across the company’s product suite. Advocate for the adoption of these technologies by demonstrating their impact on enhancing user engagement, personalization, and overall satisfaction, thereby driving competitive advantage
• Be responsible for the entire product development lifecycle from concept through launch and beyond
• Implement meticulous experimentation processes to assess product stability, performance, and readiness before launch. Post-launch, continuously supervise product performance metrics
• Establish a feedback loop with customer support to quickly address and rectify user issues, ensuring high satisfaction and retention rates
• Act as the primary recommendations product evangelist and point of contact to build awareness and understanding across all levels of the organization
• Collaborate extensively with engineering, data science, analytics, and product teams to create alignments across initiatives. Lead regular cross-functional meetings to review progress, address challenges, and adjust plans as vital to meet strategic goals
• Provide transparent and frequent updates to collaborators that highlight goals, progress against goals, and strategic adjustments. Ensure that all team members are engaged in the product's success and future directions
• Champion a culture of experimentation within the product management team by promoting A/B testing, multivariate tests, and other statistical approaches to decision making. Encourage learning from both successes and failures to continuously improve product offerings
• Harness both qualitative and quantitative data to form a complete view of the product landscape. Apply quantitative data to measure user engagement, conversion rates, and other critical metrics, while employing qualitative insights from user feedback, usability testing, and market research to understand user needs and perceptions