Saurabh G Ghatnekar

Data Scientist

Pune, Maharashtra, India8 yrs 3 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Expert in architecting scalable data platforms.
Proven track record in optimizing data workflows.
Skilled in integrating machine learning models.

Stackforce AI infers this person is a Data Engineering and Machine Learning expert in the SaaS industry.

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Skills

Core Skills

Machine LearningData EngineeringAnalyticsDevops

Other Skills

A Product Management guide to Experimentation & A/B testingAI SystemsAI algorithmsAdobe AnalyticsAmazon Web Services (AWS)Apollo GraphQLArtificial Intelligence (AI)Big DataBigQueryBusiness AnalysisCROCloudCloud-based data infrastructureComputer VisionConversion Optimization

About

Experienced ML & Data Engineer specializing in architecting scalable data platforms, integrating machine learning models, and optimizing data workflows for both structured and unstructured data. Skilled in Python, SQL, Spark, and extensive AWS services (Glue, Athena, Redshift, S3). Proven expertise in designing efficient ETL processes, seamless API integrations, and real-time data solutions. My strength lies in translating complex business requirements into actionable technical solutions, ensuring robust and cost-effective data infrastructure that drives strategic business outcomes. Core Skills: ✔ Data Warehousing & Data Lake Management ✔ Advanced SQL & Data Optimization ✔ Python & PySpark Data Pipelines ✔ AWS Cloud Services (Glue, Athena, Redshift, EMR, Lambda) ✔ API Development & Microservices Architecture ✔ Machine Learning & Computer Vision Integration ✔ Data Crawling & Automation

Experience

Measurebit

2 roles

Senior Data Engineer

Promoted

Apr 2025 – Present · 11 mos · Remote

As a Senior Data Engineer at Measurebit, I lead initiatives at the intersection of data infrastructure and modern AI systems, with a focus on:
LLMs and Agentic Workflows: Designing and orchestrating agent-based systems that leverage large language models for intelligent automation, content generation, and decision support.
LLMOps: Building robust pipelines to support the end-to-end lifecycle of LLMs—from data preparation and model deployment to evaluation and retraining.
Observability & Monitoring: Implementing metrics, logging, and tracing systems to ensure reliability, transparency, and performance across AI and data workflows.
Scalable Data Infrastructure: Maintaining and evolving Measurebit’s data platform to support high-throughput, low-latency use cases across marketing analytics and experimentation.
I collaborate with cross-functional teams to deliver AI-native solutions that drive measurable business value and innovation.

LLMOpsLarge Language ModelsData InfrastructureAI SystemsObservabilityMonitoring+2

Data & Analytics Engineer

Mar 2021 – Mar 2025 · 4 yrs · Remote

Led the design and implementation of cloud-based data infrastructure on GCP, resulting in a 40% improvement in data processing efficiency and reducing operational costs by 30% annually.
Architected and deployed enterprise data warehouse solutions using BigQuery, enabling real-time analytics capabilities that supported decision-making across five business units serving 100K+ daily users.
Engineered automated ELT pipelines using Airbyte and DBT, reducing data transformation time from 24 hours to 10 hours while ensuring 99.9% data accuracy.
Developed and integrated server-side tracking solutions across multiple platforms, consolidating data from 12+ sources into a unified analytics platform.
Built and maintained full-stack web applications using JavaScript and Apollo GraphQL, creating intuitive interfaces that improved data workflow efficiency by 60%.
Implemented comprehensive analytics solutions using Adobe Analytics and Google Analytics, providing actionable insights that drove a 25% increase in marketing ROI.
Designed and executed Media Mix Modeling (MMM) and Incrementality Testing, optimizing marketing spend allocation and accurately measuring the impact of different media channels on business KPIs.
Conducted Geo Tests to analyze regional marketing effectiveness, refining budget allocation strategies and improving campaign performance.
Conducted strategic business analysis and stakeholder management, translating complex technical solutions into business value and securing buy-in for key data initiatives.
Technical Skills:
Cloud Platforms: Google Cloud Platform (GCP)
Data Warehousing: BigQuery
Analytics: Adobe Analytics, Google Analytics
ETL/ELT: Airbyte, DBT
Development: JavaScript, Apollo GraphQL
Data Integration: Server-side tracking, Multi-platform synchronization
Marketing Analytics: Media Mix Modeling (MMM), Incrementality Testing, Geo Tests

Cloud-based data infrastructureBigQueryELT pipelinesServer-side trackingFull-stack web applicationsAdobe Analytics+5

Keito

Machine Learning Engineer (MLOps)

Aug 2019 – Feb 2021 · 1 yr 6 mos · Pune/Pimpri-Chinchwad Area · On-site

In my role as a Machine Learning Engineer at Keito, I was at the forefront of integrating AI and machine learning into scalable, real-world applications, focusing on the development of Intelligent Assistants. My expertise spanned across MLOps, DevOps, AI, image processing, and full-stack development.
Key Achievements:
MLOps and DevOps Synergy: Streamlined ML model lifecycle from development to deployment, enhancing system reliability and performance.
AI Implementation: Developed AI algorithms for Intelligent Assistants, ensuring adaptability in diverse applications.
Image Processing: Utilized advanced techniques for improved visual data interpretation in web applications.
Full-Stack Development: Contributed to both backend and frontend, ensuring seamless ML model integration.
Collaboration: Worked with cross-functional teams, fostering a cohesive approach to AI solution development.

MLOpsDevOpsAI algorithmsImage ProcessingFull-Stack DevelopmentMachine Learning

Flux auto

Deep Learning Engineer

Jul 2018 – Aug 2019 · 1 yr 1 mo · Bengaluru Area, India

Responsible for prototyping and developing State of the Art algorithms for vision-based perception and path planning for self-driving trucks

Intel corporation

Intel Student Ambassador

Nov 2017 – Aug 2018 · 9 mos · Pune

Provided training to 50 students on Python for Machine Learning. Experience of Deep Learning on Intel DevCloud.
Published article on DevMesh related to Machine Learning using Intel Architecture
Worked on object detection using Intel Movidius Stick (AI on Edge)

PythonDeep LearningObject DetectionMachine Learning