Vidya is available for hire
Hire VidyaVidya Raman
Verified Expert in Product Management
Product Manager
Location
San Francisco, CA, United States
Toptal Member Since
September 6, 2019
For over 20 years, Vidya's been successfully building enterprise software businesses in several industries ranging from telecom, healthcare, energy, and IoT. Most recently, she was the director of PM at Cloudera, leading the machine learning platform. Along with having worked in both startups and mature enterprises, Vidya excels in building platforms as well as apps. She can have deeply technical discussions and presents to the C-suite at ease.
Project Highlights
Cloud-native Platform for ML Engineers and Data Scientists
Led product definition and development. Customers span multiple verticals—autonomous driving, banking, healthcare, and more.
Neural Network-enabled Load Forecasting Application
Led the product from concept, research, development, launch to customer deployment.
Expertise
Work Experience
Director of Product Management
2018 - 2019
Cloudera
- Developed the world's most versatile data science workbench for the Hadoop platform. It is the fastest-growing product in the company with 100% YoY growth.
- Worked closely with customers who ranged from industries such as autonomous driving, healthcare, banking, and financial services, governments, telecom among others.
- Developed a portfolio strategy including pricing, roadmap, and feature set for an advanced machine learning platform.
- Analyzed several segments of the AI/ML tooling space and made portfolio recommendations including potential acquisitions and partnerships/integrations.
- Spearheaded a design partner program and worked closely with designers and architects in developing a cloud-native product.
- Developed a deep understanding of DevOps, SecOps, SREs and distributed cloud-native architecture that leverages microservices, service mesh, Kubernetes among others.
Director of Product Management
2012 - 2018
eMeter (IoT startup acquired by Siemens)
- Doubled sales in three years when the market grew at half the rate. Grew product offerings 3X in two years with flat spend and beat the plans for both years. EnergyIP® has been placed in Gartner’s magic quadrant for five years in a row.
- Led analyst and press meetings worldwide for the product line.
- Stayed in continuous contact with customers, which resulted in 100% retention and critically important referenceable, evangelistic relationships worldwide.
- Led the worldwide analytics customer advisory board for four years and received five-star reviews.
- Recruited, developed, provided growth opportunities to, and retained a high-performing team of product managers and data scientists.
- Developed the strategy, roadmap, and feature set for advanced analytics software applications that enable the world’s leading factories and energy providers to create value from IoT-generated big data.
- Had full P&L responsibility and led a team of product managers and data scientists.
- Built and sold IoT ML-enabled apps.
- Worked closely with data scientists and engineers through data prep, analysis, model evaluation, training, testing and deploying to production.
- Developed scalable apps that obtained industry-leading performance metrics (e.g., accuracy, recall, precision).
- Engendered trust in a community that mistrusted AI by choosing appropriate ML models, mitigated model risk by controlled model retraining and building features in the product that allowed side-by-side comparison of ML and non-ML approaches.
- Led the implementation of several components that accelerated analytics application development for IoT, e.g., clustering, anomaly detection, feature extraction, dimensional reduction and prediction models for different kinds of time series data.
- Collaborated with engineering to make key technology decisions around the Hadoop stack that corresponded to business needs such as optimal TCO, low latency, high throughput, etc.
- Helped on-premise customers transition to cloud (AWS and Azure).
- Developed value-based pricing models for the entire product portfolio.
Senior Product Manager
2009 - 2012
Silver Spring Networks
- Was recruited as the second product manager in a pre-IPO startup and made significant contributions to growth from sales of $3.3 million in 2009 to $196.7 million in 2012.
- Managed network automation and IoT analytics software products, including SSN’s flagship automation product, Gridscape, from inception through launch.
- Took six software products from design through successful commercialization.
- Laid the groundwork for products that automatically routed IoT-generated information to analytics applications and provided improved revenue assurance.
- Created wireframes and conducted usability tests and drove acceptance of SSN’s products.
- Worked directly with sales to acquire early customers and develop loyal, referenceable relationships.
- Onboarded several strategic partners.
- Led API definition for connecting third-party devices to SSN’s network.
- Uncovered solution gaps that created $3 million of accretive annual revenue.
Product Manager
2007 - 2009
Medtronic
- Worked as a product manager for market-leading healthcare software that provided insights from data generated from a wearable insulin pump and continuous glucose monitor.
- Used observational research techniques to glean insights into user needs, motivations, and behavior that helped define personas, scenarios and eventually vision, roadmap and feature sets.
- Demonstrated the market opportunity and obtained significant funding to execute on a new vision.
- Validated the concept and wireframes with lead customers to obtain internal buy-in and funding.
- Grew the ecosystem for partner integration with the software by 50%.
- Defined and developed an SDK that was used to integrate with three of the top four leading meter manufacturers.
Project History
Cloud-native Platform for ML Engineers and Data Scientists
Led product definition and development. Customers span multiple verticals—autonomous driving, banking, healthcare, and more.
• Conducted user studies and identified distinct user personas (data engineers, data scientists, DevOps, SREs) and associated value propositions.
• Wrote user stories corresponding to different personas.
• Developed detailed requirements for various scenarios ranging from provisioning of clusters, running workloads, management of security, governance as well as end-to-end admin and user workflows.
• Worked with UX designers in order to develop UI mocks and designs.
• Collaborated closely with the lead architect to iteratively plan and architect the product offering.
• Wrote user stories corresponding to different personas.
• Developed detailed requirements for various scenarios ranging from provisioning of clusters, running workloads, management of security, governance as well as end-to-end admin and user workflows.
• Worked with UX designers in order to develop UI mocks and designs.
• Collaborated closely with the lead architect to iteratively plan and architect the product offering.
Neural Network-enabled Load Forecasting Application
Led the product from concept, research, development, launch to customer deployment.
• Worked closely with a team of data scientists and engineers through data prep, analysis, model evaluation, training, testing and deployment to production.
• Built scalable apps that have obtained industry-leading performance metrics (e.g., accuracy, recall, precision).
• Led the implementation of several components that accelerated analytics application development for IoT, e.g., clustering, anomaly detection, feature extraction, dimensional reduction and prediction models for different kinds of time series data.
• Collaborated with engineering to make key technology decisions around Hadoop stack that corresponded to business needs such as optimal TCO, low latency, high throughput, and so on.
• Monitored and measured the usage of applications especially mapping them through the customer journey.
• Built scalable apps that have obtained industry-leading performance metrics (e.g., accuracy, recall, precision).
• Led the implementation of several components that accelerated analytics application development for IoT, e.g., clustering, anomaly detection, feature extraction, dimensional reduction and prediction models for different kinds of time series data.
• Collaborated with engineering to make key technology decisions around Hadoop stack that corresponded to business needs such as optimal TCO, low latency, high throughput, and so on.
• Monitored and measured the usage of applications especially mapping them through the customer journey.
Education
2005 - 2007
Master of Business Administration (MBA) Degree in Business Administration
Duke University - Durham, NC, USA
2004 - 2005
Master's Degree in Biomedical Engineering
University of Alabama at Birmingham - Birmingham, AL, USA
1995 - 1999
Bachelor's Degree in Electronics and Telecommunication Engineering
Bangalore University - Bangalore, India
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