Dec 2023 – Feb 2025 · 1 yr 2 mos · Remote

• - SQL, Math and Python coding to train the Codex models.

Oct 2023 – Present · 2 yrs 7 mos · Remote

• Self employed trainer
• AIML Product Manager
• DataScience, ML and Deep Learning
• Technical Writing

Aug 2022 – Feb 2025 · 2 yrs 6 mos · Bengaluru, Karnataka, India

• Working as a Platform Technical Product Manager for ML Development Infrastructure Platform which provides following
• 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭
• Formulate Product Vision Product Vision, Strategy, Goals, Value Proposition, Learn from Failures and Measure Outcomes.
• 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐒𝐤𝐢𝐥𝐥𝐬
• Data Engineering: Experience in all stages of data engineering, ETL, and ELT frameworks. Data Pipeline with Airflow, DataHub, Hevo, EMR, Spark, BigQuery, Data Lakehouse, DataBricks, S3, Athena, Sagemaker etc..
• Machine Learning Engineering: Hands on experience with supervised and unsupervised machine learning algorithms and deep learning for NLP and CV. Expertise in ScickitLearn, TensorFlow, and Keras. Have handled large-scale feature engineering with Hadoop, spark, python, airflow, Elasticsearch, MongoDB, Model runtime management, deployment automation, MLFlow, and DVC. Scaling ML Models in production using Kubernetes.
• Platform Engineering: Enable developers and data scientists to iterate faster over the models, and make the datasets available for experiments, with security compliance in place. Designing reusable assets and services for large-scale data and ml platforms with logging, monitoring, disaster recovery, and multiple deployment strategies.

Dec 2019 – Aug 2022 · 2 yrs 8 mos · Bangalore Urban, Karnataka, India

• Responsible for defining roadmap and driving the Platform of Data Engineering known as Property Datawarehouse for all the ARTs across the Organisation which supports Graph Analytics and Machine Learning system with microservice architecture used for data or feature extraction in Remote Sensing and GIS domain.
• . GraphDB, accessing microservice end point through GraphQL and designing use cases of Graph Analytics for Geospatial domain.
• . Productionization of Deep Learning models SDD, UNet, PSPNet, MaskRCNN by designing workflow for GIS domain.
• . Designing MLOps Serverless data pipeline and the driving the team in implementing it.
• . Work on Business Requirements to convert those into Technical requirements, by supporting in designing the technical workflows, design review, Epic and user stories, product backlog, and backlog refinements.
• Collaborate with multiple stakeholders including Senior Management, UX Designers, Customer Success Team, Product Marketing Manager, Sales, Engineering Teams, Vendors, Production Support Team, etc.
• Technologies: neo4j, Open Tracing,Jaeger, React js, Swagger UI, Elastic Stack, Helm, Docker, ArgoCD, AWS, Elastic Search, Go, Python, Computer Vision, NetFlix conductor, Netflix Hystix, Micro frontend architecture, Figma.

Jul 2019 – Dec 2019 · 5 mos

• LifeSphere MultiVigilance 10:
• The life sciences industry’s end-to-end safety system with production-ready automation, satisfies E2B (R2) and (R3) requirements and is fully compliant with global safety reporting standards set by health authorities like the FDA, EMA, PMDA, and NMPA. LSMV10 also provides support for Japan and China and offers Automated Case Intake, Automated Case Data Extraction, Automated Validity, Triage & Dupe Check, Automated Coding, Automated Follow-up Management, Machine Translation.

Jan 2014 – Dec 2019 · 5 yrs 11 mos

• LifeSphere Reporting and Analytics
• Objective: Bringing simplicity to periodic and ad hoc safety reporting. Leverage out-of-the-box functionality to generate data listings, conduct analysis and gather business intelligence to meet all regulatory, operational and compliance reporting requirements.

Aug 2012 – Jan 2014 · 1 yr 5 mos

• agSignals:
• Objective: Proactively identify and manage safety issues, and easily assess their impact on a product’s benefit-risk profile across its life cycle.
• Responsibilities:
• Design the application to support Safety signal detection, assessment, prioritisation and management in an automated workflow, as defined by the regulatory guidelines.
• Define the data sources, analyse the data, address the required actions in order to make those suitable for qualitative and quantitative data analysis.
• Define the Data mining algorithms, do the POC, validate those before integrating those with the application.
• Initiate a release with defined scope, manage it with Dev, QC, Technical Writers, Service team, provide the demo to customers, get the feedback and update the product backlog periodically.

Oct 2010 – Oct 2012 · 2 yrs · Bangalore

• Involved in HEDIS implementation with below business areas in data integration from various sources of CVS Caremark:
• Health Plan (HP) (Claim Processing, Member Eligibility verification, Pre-authorization, Coordination of Benefit, Member Enrolment, Formulary, Explanation of Benefit)
• Effectiveness, Availability and Experience of Care
• Utilisation Review
• Utilization and Risk Adjusted Utilization
• Accountable Care Organizations (ACO)
• Case Management (CM)
• Disease Management (DM)

Jun 2009 – Nov 2010 · 1 yr 5 mos · Bengaluru, Karnataka, India

Sep 2007 – Sep 2008 · 1 yr · Bengaluru, Karnataka, India

• Was responsible for web application development using MVC architecture in Java and PLSQL as DB.

Sep 2006 – Sep 2007 · 1 yr · Bengaluru, Karnataka, India

• Was responsible for web application development using MVC architecture in Java and PLSQL as DB.