Jul 2024 – Present · 1 yr 11 mos

• Sidebar is a private community of senior leaders, providing members with a vetted network and the leadership insights needed to drive impact in today’s rapidly changing business environment.

Feb 2024 – Jul 2025 · 1 yr 5 mos · San Francisco Bay Area · Remote

• Reporting to CTO, responsible for Data and AI Engineering - Relationship Intelligence, NLP, LLMs ( RAG , Agents) , AWS, Microservices, Spark ( DBX) , Kafka, k8s, VectorDBs, MCP
• Lead Engineering efforts
• Develop GenAI applications including our QandA Conversation AI service Deal Assist:
• https://support.affinity.co/s/article/How-to-set-up-your-account-for-Deal-Assist
• develop features around multi modal semantic search, summarization and analysis capabilities.
• Build and maintain workflows using LLMs to standardize, classify and derive insights from disparate vendor datasets.
• Work on hard data quality problems that arise due to entity management and complex data syncs.
• Work on Search services capable of indexing, retrieving, and performing semantic & vector searches across diverse CRM data points.
• Drive adoption of LLMs and ML solutions across Affinity particularly around Search, RAG, vector databases.
• Improve user experience by providing seamless and intelligent interfaces.

Nov 2021 – Apr 2022 · 5 mos

• Taught Fintech program covering all aspects in Fintech including ML, modeling ( Python, scikit learn, tensorflow), Blockchain smart contracts ( Solidity) covering Fungible and NonFungible tokens.

Sep 2021 – Feb 2024 · 2 yrs 5 mos · Toronto, Ontario, Canada

• At Loblaw Digital, I built and scaled the Data & ML platform/MLOps foundation — shaping the roadmap for Data Engineering, ML Engineering, Digital Analytics, and Experimentation. This included migrating from monoliths to microservices to support low-latency data use cases, implementing data contracts and ingestion from POS and fulfillment systems, deploying recommendation/personalization platforms (Seldon, VertexAI), and leading analytics (Snowplow, GA, Looker) at scale.
• With proven leadership across consumer-facing products and data platforms, I bring a mix of business impact and deep technical expertise: microservices, pipelines, experimentation, ML deployment, and GenAI-powered tooling. Always focused on solving complex problems, scaling teams, and enabling measurable impact across Ads, Data, and ML.
• I’ve led 50+ member orgs spanning backend, data engineering, MLOps, data science — driving $19M onsite media revenue targets through sponsored and display ads across PCX, SDM, and PCO. Delivered self-serve Sponsored Search (industry-standard CPC model), transforming the onsite ads experience for shoppers while scaling platforms for reliability and growth.
• Stack: GCP, Kubernetes, VertexAI, Seldon, Airflow, DBT, Ray, Looker, Mlflow, Snowplow analytics, Dataproc, Dataflow, Terraform to name a few!

Aug 2021 – Dec 2023 · 2 yrs 4 mos

• Data engineering, applied Ml engineering, MLOps and deep learning courses.

Feb 2020 – Sep 2021 · 1 yr 7 mos

• Primary responsibilities and work include implementation of transformational projects in Fraud Fusion area with focus on Automated solutions, Data and Analytics ( Data Engineering and Deployments of data/model pipelines), Application development, Infrastructure, Micro services.
• Use cases involved * : Internal threat detection , Fusion centres case management, Elder fraud prevention, Mule fraud detection , compromised cards in DarkWeb, Swift payment frauds.
• Explored blockchain tech for banking usecases related to fraud.
• Stack * : Hybrid ( Cloudera, Azure), Openshift, Dremio, Minio, Enterprise Anaconda, Golang, Tableau, Spark, Python

Aug 2017 – Jan 2020 · 2 yrs 5 mos

• Data Science | Cloud Engineering | Data Engineering
• Usecases: Stress testing (cmrm), Client experience, Treasury analytics, Credit risk, Payments and Fraud, Institutional trading and recommendations.
• My work involves data engineering, building AI/ML models and delivery on cloud platforms like GCP and Azure.
• Lead for AI/ML cloud platforms where we can deploy models and AI solutions at scale. My job also includes working closely with Architecture, Technology, Info Security and Governance teams in the bank.
• Stack : GCP, Azure, Python, Scikitlearn, TF, AutoML, H20.ai, Spark

Jan 2019 – Aug 2021 · 2 yrs 7 mos

• Course creator and instructor for the University of Waterloo Data science and ML certificate course.
• Taught courses : Big Data Management, Data Science fundamentals, Machine Learning

Aug 2018 – Aug 2020 · 2 yrs

• Created course content and Taught a wide spectrum of courses : Big Data Management, Data Science fundamentals, Machine Learning, Deep Learning , Artificial Intelligence.
• This was delivered for two certificates for University of Toronto's School of continuing Studies for their Data science and AI certificate programs.

Apr 2015 – Aug 2017 · 2 yrs 4 mos · Toronto, Canada Area

• Big data lead for Bell media/mobility related usecases
• Usecases - Ad measures and audience reach, IPTV analytics, Ad effectiveness, Targeting and offers.
• Stack : Hadoop, Spark, Spark MLlib, Hbase, Hive

Aug 2014 – Mar 2015 · 7 mos

• Work on Analytics application software for Telecom services across US.

Dec 2012 – Jul 2014 · 1 yr 7 mos

• Worked for the NLU( Natural Language Understanding) Data team at Nuance.
• Use cases - analyze logs for a number of Digital mobile assistants on quality of conversational AI. ( Speech to text)

May 2012 – Sep 2012 · 4 mos · Markham, Ontario

• Database query compiler and optimization team
• Working on query rewrites in the Query graph model of DB2 compiler using heuristic based optimization techniques

May 2011 – Oct 2011 · 5 mos · Montreal, Canada Area

• Nexalogy is a social media analysis company that helps its clients make better decisions through information extraction and analysis.
• During this course, I worked on a lemmatizer for both french and english and the lemmatized words were used as an input to identify "top words" from the various text sources.
• I also wrote scripts to cluster words based on statistical and clustering algorithms based on sentiments.
• text summarization/topic modelling

Sep 2010 – Mar 2013 · 2 yrs 6 mos

• Researched on the evolution of suitable data models for multi tenant databases for SaaS and working on a generalized algorithm for rewriting such queries from the tenant database schema to the cloud database schema.
• I have also researched on the Schema mapping techniques for data management in a Cloud Computing Architecture, Evaluation of TPC bench mark. I also have some knowledge in OLAP. I designed a simple OLAP system using Pentaho Kettle to implement various cube operations.
• Prior to this I was working on Uncertainity and Deductive databases and in this process acquired knowledge in Prolog.
• Big Data Research Lab:
• Worked towards optimizing Hadoop Map Reduce and suitable for BI applications.

Sep 2010 – Mar 2013 · 2 yrs 6 mos

• Partial Tution Scholarship, Concordia University
• International student tuition fee remission award, Concordia University
• Nominated for Member of Golden Key International Honour Society
• Courses Taken:
• Advanced Databases
• Artificial Intelligence
• Semantic Computing
• Advanced Programming Practices
• Design and Analysis of Algorithms

Jun 2009 – Jul 2010 · 1 yr 1 mo

• Scientometric study of journal access: The objective of this study was to collate on-line access details, quantify the total access to journal sites per day, analyze the access URL’s and identify the patterns, archive and indexing scheme at the journal site. Created an online monitoring tool showing statistical data of access and their trends.

Apr 2009 – Jun 2009 · 2 mos

• Developed an Employee Software Management tool in C#, ASP.net and SQL Server 2000.