Ravi Shankar

Director of Engineering

San Francisco, California, United States12 yrs 3 mos experience

Highly StableAI Enabled

Key Highlights

Led a global ML team driving product innovation.
Spearheaded impactful ML projects achieving significant cost savings.
Expert in deploying scalable ML solutions on cloud platforms.

Stackforce AI infers this person is a Machine Learning expert with a strong focus on E-commerce and Data Science.

Contact

Skills

Core Skills

Machine LearningTeam ManagementProduct DiscoveryComputer VisionRecommender SystemsDeep LearningData ScienceData AnalysisBusiness Analytics

Other Skills

personalized recommendation systemsML techniquesNLPGoogle GeminiDockerAirflowembedding-based similarityobject detectionLVLMspersonalized recommendationsAWSautomated toolsmodel tuningPySparkpredictive maintenance

About

I lead a Machine Learning Product Discovery & Personalization team at Overstock, through recommender systems, computer vision, NLP, GenAI(LLMs, LVLMs, Diffusion Models). I have more than 10 years of ML experience, more than 3 years leading teams. ► Team Management & Product Innovation: Manage a globally distributed ML team across the US, India, and Ireland, actively hiring in Ireland (DM for details). Engage with existing and new stakeholders to identify and explore new use cases for solving challenges with ML. ► Scalable ML Deployment: Well-versed in in-demand skills such as deep learning, natural language processing, computer vision, recommender systems, LLMs. Machine learning models at scale on cloud (AWS and GCP). Leveraging Docker, Kubeflow (Kubernetes), CI/CD pipelines for scalable workflows. and reinforcement learning. Open to roles that leverage my expertise in building and deploying machine learning solutions to build products that drive impactful results.

Experience

Dick's sporting goods

Manager of Machine Learning

May 2025 – Present · 10 mos

In this role, I lead a talented team focused on building scalable, personalized recommendation systems that power engaging and relevant athlete experiences across our omnichannel platforms. We're leveraging deep learning, behavioral data, and advanced ML techniques to shape the future of how customers discover and shop for what they love.

deep learningpersonalized recommendation systemsML techniquesMachine LearningTeam Management

Overstock

Manager II - Machine Learning Product Discovery

Oct 2023 – Feb 2025 · 1 yr 4 mos · San Francisco Bay Area

Team Management: Managing a global team of 6+ ML Engineers and Scientists across the US, India, and Ireland, fostering collaboration and driving innovation in ML projects.
ML Projects: Spearheaded the development of a content restructuring model (and improved product knowledge graph) using deep learning (using computer vision, NLP) and Google Gemini (LLMs + RAG), making it easy for our partners to onboard new SKUs. Reduced duplicate products by over 50% with embedding-based similarity and pHash, boosting customer engagement. Championed usage of LVLMs (BLIP, Gemini Flash, ChatGPT) for product attribute prediction, leading to improve search results and engagement. Used deep learning (neural networks) to identify similar items and identify outliers for making prices competitive. Deployment on GCP and on-prem using Docker and Airflow.
Product Discovery & Recommendations: Championed the use of in-house recommendation (combination of matrix factorization, collaborative filtering, aesthetic similarity, association rule learning) algorithms on new business verticals - Overstock and Zulily, achieving over $2M in cost savings. Directed the 'Shop the Room' project using object detection using Segment Anything Model (SAM), LVLMs (Gemini-Flash, ChatGPT) for personalized recommendations, resulting in higher average order sizes.
Stakeholder Engagement: Engaged with multiple stakeholders to identify new ML use cases, aligning the ML product vision with business goals to drive impact.

deep learningcomputer visionNLPGoogle GeminiDockerAirflow+2

Verisk

Machine Learning Lead

Jun 2018 – Oct 2023 · 5 yrs 4 mos · San Francisco Bay Area

Team Lead: Managed a team to build ML solutions to fight fraud, automate claims - leverage AWS and deep learning (computer vision, natural language processing) for insurance industry. Product built: https://www.verisk.com/products/digital-media-forensics/
ML Solutions: Applied state-of-the-art computer vision techniques—image classification, object detection, and instance segmentation built in Tensforflow/ Pytorch —to build products to detect fraudulent claims. Set the strategic vision for the image & document editing detection product, aligning development efforts with stakeholder expectations.

computer visionNLPAWSdeep learningMachine LearningTeam Management

Conversica

Machine Learning Scientist

Sep 2017 – Jun 2018 · 9 mos · Greater Seattle Area

Built ATHENA (PySpark), an automated tool for building and tuning machine/ deep learning models text data, saving hundreds of hours on model building
Built a algorithm (machine learning + sentence similarity) to tag unlabeled text bypassing human annotation to generate larger corpus for training machine learning and deep learning models
Built and maintaining self-learning machine learning (logisitc regression) and deep learning (charCNN) pipelines in production
Built pipeline to work with non-English data within the current setup using Google Translate
Use PySpark to distribute extensive computations (ml models + grid search + generating new data)

automated toolsmodel tuningPySparkMachine LearningDeep Learning

Molekule

Machine Learning Intern

May 2017 – Aug 2017 · 3 mos · San Francisco Bay Area

Lead setup of cross-device attribution and user journey; exploring use of Markov models to credit sales to device - mobile & Desktop
Developing logic for predictive maintenance of air filters for timely replacement using pattern mining
Developed Tableau dashboard & algorithm for early detection of non-performing ad sets on Facebook

predictive maintenancepattern miningTableauData ScienceMachine Learning

University of connecticut

Graduate Research Assistant

Sep 2016 – Jul 2017 · 10 mos · Greater Hartford

Built a scalable system (using multiprocessing in Python) to find similarity between thousands of documents using difflib Sequence Matcher/ Levenstein Distance /cosine similarity/ word embeddings generated by word2vec & glove
Code at https://github.com/analyticsbot/document-similarity
Analyzed Stackoverflow data to understand the factors that determine a user’s reputation
Code at https://github.com/analyticsbot/stackoverflow

similarity algorithmsdata analysisData ScienceMachine Learning

Fidelity investments

Data Analyst

Sep 2015 – Jul 2016 · 10 mos · Bengaluru, Karnataka, India

Worked with Marketing to analyze/predict participant loan behavior in the three-to-six month period
Worked closely with the marketing team to add digital capability ensuring data driven decisions
Leveraged click stream data from www.netbenefits.com to improve participant experience and marketing effectiveness. Used D3.js for the senior management to demystify participant web journeys, adding efficiency in decision making
Analyzed and optimized Fidelity's 401k related marketing campaigns. I was part of a team tasked with understanding our participant's journeys and digital activity, helping participants to save more in their 401(k) plans
Conducted Python training sessions for colleagues, adding new capability

data analysisdigital capabilityData AnalysisMachine Learning

Latentview analytics

Data Scientist

May 2014 – Sep 2015 · 1 yr 4 mos · Greater Chennai Area

Implemented an user-preference based recommendation engine product - JARVIS (Java, Mahout, Hadoop, Spark, Cassandra, RabbitMQ), now one of four flagship products of the company
Team Received nomination for "Spirit of LatentView Award".
Created internal social media analysis product - SocioBOT (Python), after understanding the problems faced by in-house teams, saving hundreds of hours of manual work.
Developed a clustering approach for path-to-purchase analysis to identify high frequency path sequence and high drop off pages for an e-commerce client (Python, D3.js, SQL, Excel).
Developed several executive-level Tableau dashboards that integrated forecasts and business performance metrics contained in various SQL tables for effective data visualization (Tableau).
Web scraped multiple review websites, performed text mining to extract sentiment to identify innovation and purchase driver indicators and supervised creation of Tableau dashboards for senior management for a US retail client (Python, Scrapy).
Planned, organized, and executed a company-wide Hackathon, involving more than 200 participants, to push the interaction of new technologies and paving way for future hackathons.

recommendation enginesocial media analysisData ScienceMachine Learning

Zipdial mobile solutions pvt ltd. (acquired by twitter inc.)

Business Analyst

Jun 2013 – May 2014 · 11 mos · Greater Bengaluru Area

Implemented a predictive model to improve efficiency of ZipDial’s online marketing campaigns by predicting the customer response.
Offered strategic & tactical insights to clients by developing excel dashboards on using campaign data.
Involved in End-to-end Project management including requirement analysis and client management.

predictive modelingcampaign analysisData AnalysisBusiness Analytics