Aryan Solanki

Associate Consultant

Mumbai, Maharashtra, India1 yr experience

AI EnabledAI ML Practitioner

Key Highlights

Hands-on experience in AI-driven applications.
Strong foundation in machine learning and data science.
Leadership role in organizing technical summit.

Stackforce AI infers this person is a Data Scientist with a focus on AI and Machine Learning in a startup environment.

Contact

Skills

Core Skills

Data ScienceMachine LearningDeep LearningSoftware Development

Other Skills

A/B TestingUser SegmentationModel DeploymentAnomaly DetectionModel QuantizationFairness MetricsPyTorchPythonCross-team CollaborationConversational AIAWSRAG PipelinesLLM BenchmarkingCommunication

About

I’m a junior (3rd year) at the Indian Institute of Technology Gandhinagar, majoring in Artificial Intelligence with honors. I combine my love for coding and technology-driven businesses with a deep curiosity about software, machine learning and data science. With hands-on experience in developing AI-driven applications and more, I’m currently pursuing machine learning research in the domain of hardware accelerators. And I am looking forward to join Goldman Sachs as a Summer Analyst (Engineering) in the upcoming Summer. Summer 2025, I interned at MPL (Mobile Premier League) as a Data Scientist. This gave me the opportunity to deploy real world code and work collaboratively across verticals in a startup ecosystem. In the past, I completed a data science internship at 86400 (formerly Mobileware Technologies) and an AI-engineer internship at a pre-seed startup. I helped this team apply to YC Spring 25. These experiences have honed my problem solving abilities and refined my skills in Python development, AWS, CrewAI, PyTorch, PySpark and more. I am also fluent with data structures and algorithms in cpp. I also served as the overall Finance and Administration Coordinator for my college's technical summit, Amalthea, demonstrating my leadership and organizational abilities. Feel free to reach out to me at solanki.aryan.ai@gmail.com or aryan.solanki@iitgn.ac.in

Experience

Nanodc lab, iit gandhinagar

Student Researcher

Aug 2025 – Nov 2025 · 3 mos

Mobile premier league (mpl)

Data Scientist (Intern)

May 2025 – Aug 2025 · 3 mos · Bengaluru, Karnataka, India

Worked as a part of the New user and Onboarding vertical of the Data Science Team.
Revamped referral propensity model with hour-wise features and stratified user cohorts (new, mid, old), improving targeting logic; designed deployment-ready pipelines with constraints on user payload delivery.
Designed and executed churn propensity–based A/B experiments (Opinio new & repeat users) by integrating ML-driven user segmentation into live product interventions.
Enabled data-driven product growth by operationalizing A/B experiments (WPS & Bingo), directly supporting higher user stickiness and incremental revenue gains.

Data ScienceMachine LearningA/B TestingUser SegmentationModel Deployment

Stealth startup

AI Software Engineer

Dec 2024 – Mar 2025 · 3 mos

Worked on a cross teams collaboration and observability platform for agentic frameworks. Helped the team apply for YC Spring 2025. Spearheaded development of the core python module.

PythonCross-team CollaborationSoftware Development

Fellowship.ai

Data Science/ML Fellow

Oct 2024 – Oct 2024 · 0 mo · Remote

Selection followed by acceptance and then withdrawal owing to other commitments.

Indian institute of technology gandhinagar

2 roles

Undergraduate Researcher

Promoted

Aug 2024 – Apr 2025 · 8 mos

Project 2: Extending Modality in Deep Autoencoding Gaussian Mixture
Model for Unsupervised Anomaly Detection
Worked under Prof. Anirban Dasgupta
The goal of this project is to improve the existing DAGMM architecture to be used for anomaly detection in images.
Project 1: Fairness of Model Quantization in Facial Expression Recognition
Worked under Prof. Manisha Padala
Investigated the impact of model quantization on fairness using the CelebA dataset.
Implemented Post Training Quantization (PyTorch) to reduce model size by 3.93x while evaluating fairness metrics like Equalized Odds (EO) and False Positive Rate Difference (FPR).
Applied techniques such as FairALM (Augmented Lagrangian Method) and Calibrated Equalized Odds post-processing to mitigate fairness gaps without compromising accuracy.
Highlighted the trade-offs between model compression and fairness, showcasing approaches to integrate fairness constraints into compressed neural networks.

Deep LearningAnomaly DetectionModel QuantizationFairness MetricsPyTorchMachine Learning

Student Leadership Conclave, Organizer

Jan 2024 – May 2024 · 4 mos

86400 (previously mobileware technologies)

Data Science Intern

May 2024 – Jul 2024 · 2 mos · Mumbai, Maharashtra, India · On-site

Built a production-ready RAG-based conversational agent for query resolution on NPCI circulars and company documents.
Evaluated multiple LLMs (Llama & Mistral) on AWS Bedrock for optimal information retrieval and response generation.
Gained expertise in AWS Bedrock, Llama, Mistral, RAG pipelines, and LLM benchmarking techniques.
Recognition as the first data science intern at the company, deploying an AI solution to enhance information accessibility.

Conversational AIAWSRAG PipelinesLLM BenchmarkingData Science