ABOUT ME

SHRAVANKUMAR
HIREGOUDAR

shravankumarhiregoudar@gmail.com
LinkedIn | Portfolio | Medium

Over the past 5 years, I’ve taken the lead on numerous data and AI projects that highlight my ability to deliver comprehensive solutions with significant impact on businesses. My edge comes from more than just my technical skills; it’s also about how I connect with clients and businesses. I excel at understanding their needs and crafting tailored solutions to address those specific challenges effectively.

EDUCATION

Rutgers Business School, Rutgers University, NJ

Master of Science in Information Technology and Analytics

08/2018 – 12/2019

Data Science, Statistics and Machine Learning, Data Analysis and Decision Making, Business Data Management, Web Analytics, Marketing Management, Time Series Analysis, Analytics for Business Intelligence

B V Bhoomaraddi College of Engineering & Technology, Hubli, India

Bachelor of Engineering in Computer Science and Engineering

06/2014 – 05/2018

Data Mining and Business Analysis, Applied Statistics and Probability, Database Management Systems, Software Engineering, Data Structures and Algorithms, Programming in python

WORK EXPERIENCE

06/2024 – CURRENT

AI/ML – PRODUCT OPERATIONS | INSIGHTS

06/2024 – CURRENT

Leading the efforts to identify and eliminate friction points in our products by leveraging AI/ML techniques.

11/2020 – 06/2024 (~3.5 years)

CONSULTANT – DATA & ANALYTICS

01/2022 – 06/2024

➊ AI Practitioner
Led the forefront of the Generative AI technical transformation for 14 unique clients and 20+ teams across industries, bringing in $3M in revenue. Developed the debut LLM solutions for 5 of these teams. Additionally, facilitated AI workshops and developed frameworks to enable the rapid transformation of GenAI ideas and use cases into actionable solutions to drive business value and broader organizational impact.

Developed and deployed a comprehensive E2E solution, connecting Azure services (AI search, Doc Intelligence, SQL DB) alongside OpenAI’s chat and embedding models to engineer a state-of-the-art information retrieval platform. Boosted unstructured multi-source information processing and retrieval efficiency, achieving a 70% faster response rate over traditional search methods.

➋ ML Engineer
Transformative impact on issue management by implementing a custom summarization model, seamlessly fused with a Markovian method, synthesizes data from diverse streams, delivering instant, prioritized alerts. By offering a centralized view of top data issues on a Python flask application, this innovative solution optimized operations and delivered a 35% increase in business performance.

➌ NLP Engineer
Revolutionized organizational change management by leveraging employee feedback data through advanced sentiment analysis and topic modeling techniques. This provided actionable insights to executives and leaders, empowering them to prioritize and develop effective change strategies, leading to a marked improvement in the planning, implementation, and communication of change initiatives by 30%.

ASSOCIATE CONSULTANT – DATA & ANALYTICS

11/2020 – 01/2022

➊ Data Architect
Integrated client’s delivery and customer-related data from EDL to the azure CDL by providing a data strategy for Consumer and Medical Devices across NA and EMEA that compliments and leverages the enterprise CDL. Identified client key stakeholders, analyzed the current state architecture, and performed a gap analysis to document high-level As-Is Architecture of source systems along with the priority of migration.

➋ Data Visualization Specialist
Transformed client operations by migrating their on-prem data to the powerful Azure cloud, unlocking a wealth of new opportunities. Delivered real-time, visually impactful representations of historical and projected provider data through executive dashboards powered by PowerBI, resulting in a 12% boost in client revenue.

⦿ Developed and rolled out an ML community of practice and training programs for new analysts and business consultants that increased ML projects across the market and helped beginners get started with ML.

06/2019 – 10/2020 (~1.5 years)

DATA SCIENTIST

02/2020 – 10/2020

Client: United States Air Force (USAF)

Implemented field-level aviation fuel contamination analysis via an integrated suite of miniaturized sensors, including NIR Spectroscopy for USAF, assembled a unique sensor by integrating the hardware components and accessories for VIS, NIR & MIR sensing
Achieved 95% classification accuracy and over 80% R2 values for predicting property of fuel. Applied SVD and PCA to perform Multi-Block data analysis to decide the best sensor combination, and the results were integrated in an IOS application

Client: Pharmaceutical company

Implemented on-going research paper on Process Analytical Technology (PAT) to monitor low dose formulation in a table press feed frame using spatially resolved Near-Infrared spectroscopy by applying machine learning techniques
Evaluated the effect of physical interface on API concentration by building PLS and SVR models and achieved 99.2% prediction accuracy on the concentration of the tablets. Further, proved ML models performed 8% better than linear techniques such as PLS

DATA SCIENTIST CO-OP

09/2019 – 12/2019
Client: United States Department of Agriculture (USDA)

Succeeded in predicting soil macronutrients for precision agriculture using miniature sensor and ML, which allows the farmer to adjust fertilizer nutrient application rates based on local requirements resulting in a tremendous increase in yields of crops
Responsible for a major modification to the approach which reduced the cost of the sensor by 60% and enhanced the performance by 350% compared to the traditional method

DATA SCIENTIST INTERN

06/2019 – 08/2019
Client: A large Winery

Applied Support Vector Regressor by running computational experiments and fine-tuning the model parameters to predict the sugar and alcohol level in the Gallo wine and achieved 96% test accuracy
Improved results by developing RF feature selection and outlier detection and rebuilt the RF and KNN models on these selected features to achieve 98% test accuracy. Deployed the project on a product which is currently being manufactured and scaled

UNDERGRADUATE RESEARCH ASSISTANT

07/2017 – 05/2018
Research Paper Publication

Designed a voice-based interface to communicate with the database using Python, SQL, Speech Recognition System, Natural Language Processing concepts. Hence, to enhance efficient interaction between user and DBMS
Performed comprehensive research on existing literature on natural language processing and speech recognition engine to identify the issues and overcome them by adding the synonym table for better mapping results which resulted in 96% accuracy
Published research paper: International Journal of Research in Signal Processing & Communication System Design 4 (2), 2018, 01-05

CAPSTONE PROJECT – RESCUE THE FARMERS

07/2016 – 04/2017

Big data analytics project

Performed a case study to understand the flaws in the current agricultural product bidding process by interviewing the farmers and traders; Conclusion: Agricultural products of the farmer was not given a fair price during the local bidding process by the traders
Built a mobile application that predicts the cost of the agricultural product based on the twenty years of previous records and allows the farmer to set his price.
The database was stored in hive tables in AWS, and the data analysis is achieved by using map-reduce functions of Hadoop using SQL, and the results are displayed on the android application.
Boosted customer satisfaction by 40% and mobile users by 350% in 2017. GitHub

KEY SKILLS

Data Fields: ML, AI (Generative and Predictive), NLP, Data Engineering, Statistics, A/B Testing
Cloud: Azure, AWS, Databricks, ETL (Matillion, Talend)
Visualization: Power BI, Tableau, PySpark
Language: Python, R, SQL

CERTIFICATIONS

AWS Machine Learning – Specialty

Microsoft Certified: Azure AI Fundamentals

Reltio MDM Configuration Specialist

GCP Generative AI fundamentals