
AI, Data Science & Applied ML at Volvo Cars
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A Senior Data Scientist with 7+ years of experience in developing data-driven solutions for various business functions (Automotive, Healthcare, Transportation). Currently, Data Scientist for Volvo cars working on solving automotive business & research problems using ML & AI. Data Science and Entrepreneurship graduate from KTH Royal Institute of Technology & Eindhoven University of technology.
KTH Royal Institute of Technology
Master’s Degree, Data Science
January 1, 2016 – January 1, 2017
EIT Digital Alumni
Minor in Entrepreneurship, Entrepreneurship/Entrepreneurial Studies
January 1, 2015 – January 1, 2017
Eindhoven University of Technology
Master’s Degree, Data Science
January 1, 2015 – January 1, 2016
Savitribai Phule Pune University
Bachelors of technology, Bioinformatics
January 1, 2008 – January 1, 2012
Volvo Cars
Data Scientist & Feature Lead
April 1, 2018 – Present
Gothenburg, Sweden
SciLifeLab
Data Scientist
January 1, 2017 – February 1, 2018
Stockholm, Sweden
National Center for Cell Science
Data Scientist / Computational Biologist
February 1, 2013 – February 1, 2014
Pune Area, India
ATG LAB
Research assistant and Jr. Faculty in Bioinformatics and Molecular Biology
August 1, 2012 – January 1, 2013
Pune Area, India
Convolutional Neural Networks for classifying protein localisation in florescent microscopy data
March 1, 2017 – June 1, 2017
This project was done as a part of The CYTO 2017 Image analysis challenge where the aim was to classify fluorescence microscopy images from the Human Protein Atlas database (www.proteinatlas.org) based on subcellular protein localization. I performed an end to end project for automated classification of subcellular protein localizations in cells using Computer Vision, Deep Learning and Transfer Learning.
Deep Learning For Image Super resolution on florescent microscopy Images
February 1, 2017 – August 1, 2017
Image Super Resolution (SR) is a process of converting a low-resolution image to a high-resolution image. I accomplished this using Deep Learning based methods on fluorescent microscopy images from The Human Protein Atlas database. - Designed and implemented a Convolutional Neural Network for SR. - Designed and implemented a Generative Adversarial Network for SR.
Artistic Style Transfer Using Deep Learning
December 1, 2016 – January 1, 2017
- Implemented the paper "A Neural Algorithm of Artistic Style" by Gatys et al. for recomposing original images in the style of other images (Like in the app prisma).
Computational Humor Research
September 1, 2016 – December 1, 2016
In a course on research methodologies at KTH we used R and Matlab in order to analyze a standup comedy recording. We quantitatively measured the effect of positive and negative language-use in jokes on the duration and amplitude of the following laughter outburst. The results were presented at the 7th annual Humor Research Conference (HRC) 2017 in Dallas, Texas, USA.
Visualization: Bike Sharing Data
December 1, 2015 – January 1, 2016
We visualized the Hubway bike sharing data using D3.js The data is available at: http://hubwaydatachallenge.org/. view https://www.youtube.com/watch?v=Rdz6zWIl_Wk for demo
Technology Entrepreneurship: Smart bag Inc
October 1, 2015 – December 1, 2015
In this project we had to undergo several phases of idea generation in order to arrive at a potential innovative businessmodel. We then had to evaluate the businessmodel by talking to potential customer, evaluating financial prospects (costs and revenue) and evaluating the risks involved. Finally we did a "startup-style" elevator pitch video. The project was part of the TU/e course “1ZM20 Technology Entrepreneurship”.
Vehicle Fleet Optimization
April 1, 2014 – July 1, 2014
An Environment and waste management enterprise collected its trip level transaction data and also GPS vehicle tracking data. I was involved in extracting patterns, anomalies, and actionable insights from this data to efficiently come up with the optimized way to use their resource and also to improve their business. Techniques Used : Linear regression,Decision Trees,Naive Bayes,Random Forests,Longitudinal Models,Support Vector Machine for regression. Tools : R,Apache Mahout
Developing robust patient adherence models and frameworks
January 1, 2014 – January 1, 2014
In health care industry non-compliance with medication regimens is a huge problem with socio-economic consequences. Due to non-adherence, pharmacy retailers lose money. More importantly, people get sick and there is healthcare expense. Patients who are on chronic diseases are expected to take their drugs periodically but they do not always follow the prescribed medication as directed. An easy way to measure this is whether they are buying the medicines at the supposed intervals. For example, if a patient bought 90 capsules and he is supposed to have 3 capsules a day, he must come back before 30 days for buying next dose. If they do not come, they are non-adherent. A leading largest pharmacy retailer has collected huge data of patient transactions (fills of their medicines at each month).To improve the medication adherence, the client believes that engaging patients is one of the best ways the client plans to proactively target those members who are at risk. The client needs a model that can account for the risk of non-adherence per patient and predict if the patient is likely to non-adhere.
Studies on bacterial gene integration in The mosquito genome
February 1, 2013 – February 1, 2014
In this project we examined the relationships of different mosquito species(Aedis egypti,Anopheles Stephensi,Culex quinquefasciatus,Anophelous ganmbiae) with endosymbiants specifically Wolbachia. By genome analysis of both the mosquito genomes and wolbachia genome an investigation was performed to examine the possible gene integration of endosymbiants in the mosquito genome.
Studies on Bacillus subspecies group bacterium isolated from Indian currency note by RNA dependent RNA polymerase Beta subunit, Nucleotide and Amino acid sequence analysis for molecular differentiation.
November 1, 2011 – August 1, 2012
The rpo b gene which encodes the b subunit of RNA polymerase was selected a single gene candidate for differentiating and studying closely selected isolates of Bacillus cereus group of bacteria. rpo b gene was selected as a molecular marker for studying B.Anthracis/cereus bacteria isolated from Rs. 10 Indian currency note due to its presence as a single copy in the genome which makes it unique unlike 16S rRNA which is present in multiple copies. Nucleotide NCBI Published sequences : http://www.ncbi.nlm.nih.gov/nuccore/?term=gawande+s+lingojwar Protein NCBI Published sequences: http://www.ncbi.nlm.nih.gov/protein/?term=gawande+s+lingojwar
Mastering LLMs: A Conference For Developers & Data Scientists
Maven
June 24, 2026 – Present
Certificate in Engineering Excellence in Big Data Analytics and Optimization
Language Technologies Institute (LTI) of Carnegie Mellon University (CMU), International School Of Engineering.
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from deep learning applications to computational humor and bioinformatics, demonstrates a broad intellectual curiosity and adaptability. Experience in both industry (Volvo Cars, SciLifeLab) and academic research (KTH, Eindhoven, NCCS) suggests comfort in various work environments. The entrepreneurial minor and project indicate a proactive, problem-solving attitude, which aligns well with innovative teams. The target role of ML Engineer is well-aligned with the candidate's deep learning and MLOps experience.
Soft Skills & Operational Fit
The candidate's experience as a Feature Lead at Volvo Cars indicates leadership, project management, and collaboration skills. Involvement in research projects and supervision suggests mentorship and initiative. The diverse project portfolio, including entrepreneurial endeavors, points to a proactive and innovative mindset. The detailed project descriptions suggest good communication of technical work.