Piyush Goyal

Data Scientist

Gurugram, Haryana, India3 yrs 10 mos experience

AI ML PractitionerAI Enabled

Key Highlights

Delivered end-to-end AI/ML solutions across diverse industries.
Expertise in building scalable machine learning systems on cloud platforms.
Proven ability to drive measurable business impact through data-driven solutions.

Stackforce AI infers this person is a Data Scientist with expertise in Fintech and Retail, focusing on AI/ML solutions.

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Skills

Other Skills

A/B TestingAI AgentsAlgorithmsAmazon Web Services (AWS)Analytical SkillsApache AirflowApache KafkaApache SparkArtificial Intelligence (AI)AzureBig DataC++Computer VisionConvolutional Neural Networks (CNN)Data Analysis

About

Data Scientist with over 3.5 years of experience delivering end-to-end AI/ML solutions across industries including retail, e-commerce, and fintech. My work focuses on building scalable machine learning systems, deploying models to production on cloud platforms such as AWS and Azure, and solving complex business problems using data-driven approaches. My technical strengths lie in Generative AI, Natural Language Processing (NLP), Computer Vision and Classical ML. I have hands-on experience with LLMs, embeddings, and tools like Hugging Face, LangChain, PyTorch, and Transformers. I’ve successfully led projects across the full ML lifecycle—from data collection and model development to deployment, monitoring, and iteration—often in fast-paced, cross-functional environments. I am highly adaptable to the evolving AI landscape and take pride in my ability to quickly learn and implement emerging technologies. Alongside technical implementation, I focus on delivering measurable business impact, whether it's through automation, predictive modeling, or customer insights. I’m also experienced in using Python, SQL, Airflow, Git, Docker, and Fast APIs for building production-grade pipelines. Graduated from BITS Pilani, I am seeking roles in Data Science, AI Engineering, or Applied ML where I can contribute to building intelligent systems that solve real-world problems at scale.

Experience

3 yrs 10 mos

Total Experience

3 yrs

Average Tenure

10 mos

Current Experience

Snapdeal

Senior Data Scientist

Aug 2025 – Present · 10 mos · Gurugram, Haryana, India · On-site

Jio platforms limited (jpl)

2 roles

Data Scientist

Aug 2023 – Aug 2025 · 2 yrs

1. Designed and implemented an end-to-end platform for customer analytics, enabling business stakeholders to curate customer cohorts for objectives like fraud detection, regular, dormant, churn risk, and VIP identification. Integrated community detection within customer graphs to help non-technical stakeholders understand technical results.
2. Created an MLOps platform integrating tools like MLflow, Kubeflow, Dagshub to help standardize machine learning pipelines and monitor deployed solutions effectively.

Data Scientist

Jul 2022 – Jul 2023 · 1 yr

1. Developed dynamic pricing solution leveraging machine learning, forecasting and optimization techniques, achieving improved gross margins upto 5% while meeting revenue targets for retail.
2. Led the development of an end-to-end micro-service for AJIO, predicting return probabilities before purchase at both item and cart level with over 75% accuracy. Capable of reducing returns at platform level by 20%. Deployed machine learning models as horizontally scalable FASTAPIs capable of handling 1000 TPS with <6ms latency.
3. Built a robust system leveraging LLMs for extracting data from diverse unstructured sources like PDFs, images and text files. Enhanced efficiency and accuracy of data extraction processes.

Deutsche bank

Financial Analyst Internship

Aug 2021 – Dec 2021 · 4 mos · Mumbai, Maharashtra, India · Remote

1. Produced 200+ sensitivity and risk analytics reports to calculate Value at Risk (VaR) and Stressed VaR (SVaR) for daily market risk assessments by team at London office.
2. Automated global equity market risk reports using Python and Excel VBA improving efficiency by ~70%
3. Curated a training module outlining 30+ BAUs to aid ~50+ new hires annually in risk modeling, portfolio scenario analysis and ETL processes.