Job Description

Our client gives AI powered business intelligence solutions. Our client is seeking a visionary Product Lead to drive our data sciences and AI/ML product portfolio. This is a strategic leadership role at the intersection of advanced technology and business impact, combining deep technical knowledge with product management expertise. You will define product strategy, lead cross-functional teams, and scale technical innovations from concept to market success-while delivering exceptional value to clients and maintaining a competitive edge in the Business Intelligence (BI) and analytics space.Key Responsibilities: Strategic Product Leadership- Define and execute a comprehensive product strategy for AI/ML-powered solutions.- Develop and maintain product roadmaps aligned with market trends and customer needs.- Own the product vision and competitive positioning across BI and data analytics domains.- Lead collaboration across Engineering, Data Science, and Go-to-Market teams to drive product success.Technical Product Management- Oversee the end-to-end development of ML-powered products that solve complex business problems.- Integrate advanced AI/ML capabilities, including LLMs, NLP, and agent frameworks.- Promote best practices in data architecture, algorithm development, and model deployment.- Drive innovation in areas such as vector databases, embedding-based retrieval, and advanced analytics.Market & Client Focus- Conduct market research and competitive landscape analysis to identify strategic opportunities.- Translate technical capabilities into differentiated, customer-centric value propositions.- Lead client advisory sessions to gather feedback, validate solutions, and optimize product-market fit.- Ensure measurable business impact and ROI across a diverse set of enterprise clients.Team Leadership- Build and mentor high-performing product and technical teams.- Cultivate a culture of innovation, technical excellence, and customer-centricity.- Implement frameworks for skill development, knowledge sharing, and team collaboration.- Drive adoption of emerging technologies and modern development methodologies.Business Impact- Support P&L ownership for the data sciences product portfolio.- Define and monitor key metrics such as adoption, retention, and revenue contribution.- Lead product launches and market entry strategies.- Collaborate with Sales, Marketing, and Customer Success for effective go-to-market execution_Required Qualifications : Technical Expertise- Master's or PhD in Data Science, Computer Science, Statistics, or a related discipline.- 8-12 years of experience in data science, machine learning, or technical product management.- Strong expertise in ML algorithms, statistical modeling, and real-world AI/ML applications.- Proficiency in Python or R, SQL, and modern ML frameworks and libraries.- In-depth knowledge of NLP, LLMs, agent frameworks, and contemporary AI/ML architectures.- Experience with big data technologies, cloud platforms (e.g., AWS, Azure, GCP), and scalable data processing systems.Product Leadership- Minimum 5 years of senior product management experience, including 3+ years in leadership roles.- Proven success in launching and scaling complex B2B technical products.- Experience in the BI, analytics, or data sciences industry.- Demonstrated ability to lead product strategy, roadmap development, and cross-functional teams.Business & Leadership Acumen- Strong understanding of the enterprise software, data analytics, and BI markets.- Experience with product monetization, pricing models, and revenue optimization.- Comfortable working with C-level executives and influencing strategic direction.- Excellent communication skills with the ability to convey complex technical concepts clearly.- Experience in dynamic, high-growth environments or fast-paced technology organizations.Preferred Qualifications:- Experience with vector databases, MLOps, and enterprise-grade ML systems.- Background in startups or scale-ups within the technology or SaaS domain.- Exposure to enterprise software sales, customer success, and retention strategies.- Track record of successful product exits or leading organizations through scale.- Familiarity with data governance, security, compliance, and privacy regulations (e.g., GDPR, HIPAA).To take this discussion further , kindly write in strict confidence (ref:updazz.com)