Data Product Management Expertise
Driving Business Value through Data
End-to-End Data Product Ownership
I manage the entire lifecycle of data products—from ideation to retirement. Whether launching new products or optimizing existing ones, I ensure each delivers maximum business value, aligning with strategic goals and user needs. I am an expert in syncing Product Lifecycle with Software Development Lifecycle by collaborating with various teams in the Organization.
As a seasoned Data Product Manager, my expertise are in transforming complex , structured and unstructured data into meaningful and actionable insights that generate business growth. My vision revolves around managing full lifecycle of data products, from ideation to launch to enhancement and retirement, while ensuring that every product and its feature aligns with business objective. Here's is a breakdown of how I bring value to Data Product Management:
Roadmap Creation & Strategic Alignment
I design product roadmaps that prioritize features based on business goals, customer needs, and market opportunities. By collaborating with key stakeholders, I ensure the roadmap adapts to evolving priorities, delivering the right product/feature at the right time.
Prioritization & Product Delivery
I prioritize features based on business value and feasibility, ensuring teams stay focused on high-impact tasks. By rightly defining MVPs, MVDs and adapting to evolving requirements, I drive the timely delivery of valuable data products. I leverage Impact-Effort Matrix for prioritizing tasks to determine which tasks to focus on, and in which order.
Requirements Gathering & Stakeholder Collaboration
I collaborate with cross-functional teams—Business Users, Various Stakeholders, Data Analysts, Engineers, Business Analysts, and Leadership to translate business and customer needs into actionable features. By fostering strong alignment, I ensure the delivery of high-impact data products.
Delivering innovative AI/ML solutions
I have successfully led the development and management of predictive models, applying statistical methods like Hypothesis testing to define the problem and success, relevant feature selection, and using hyperparameter tuning and regularization techniques to optimize performance of the model. I am proficient in using CRISP-DM framework, utilizing data analysis tools such as SQL, Python and Alteryx. With hands on experience in defining and monitoring Data Quality rules and ensuring Ethical AI practices and addressing bias. My expertise in establishing model maintenance techniques like Scheduled and Triggered Training have ensured that ML models remain accurate and adaptive to new data.