Headline

Data Scientist II at Reliance Retail| Agenic AI | Deep learning| Big data | MLOps

About

I am a Data Scientist with over 6 years of experience specializing in Machine Learning, Deep Learning, and Generative AI. My expertise lies in predictive modeling and data-driven strategies that optimize business operations. I have a strong background in fine-tuning large language models and developing advanced AI solutions that drive actionable insights. My passion for data science is complemented by my ability to translate complex datasets into strategic business decisions, enhancing profitability and operational efficiency. Throughout my career, I have successfully implemented various machine learning models and frameworks, achieving significant results such as a 75% accuracy in fashion trend forecasting and a 60% reduction in fraud through real-time detection models. I am proficient in a range of technologies including Python, TensorFlow, and cloud platforms like GCP and AWS. My goal is to leverage my skills in data science to create innovative solutions that address real-world challenges. Key Achievements: - Achieved up to 95% accuracy in predictive modeling and forecasting, significantly reducing operational inefficiencies. - Developed a GenAI taxonomy pipeline that extracts apparel attributes with an accuracy of 80-95%. - Improved credit collections by 30% and product propensity by 25% through optimized data strategies.

Location

Bengaluru

AI stack

codex

claudecode

Work experience

Data Scientist II at Reliance Retail, Nov 2024 - Present · 1 yr 10 mos, Bengaluru, Karnataka, India, In my current role at Reliance Retail, I focus on forecasting fashion trends using advanced machine learning techniques such as N Beats and XGBoost. I have successfully achieved approximately 75% accuracy in inventory optimization. Additionally, I built a Generative AI taxonomy pipeline utilizing GPT 4o, which extracts apparel attributes with an accuracy range of 80-95%. My contributions also include developing a PLM style mapping tool that filters out around 40% of non-matching catalog styles, ultimately delivering actionable insights for merchandising and product planning. Achievements: - Forecasted fashion trends with ~75% accuracy for inventory optimization. - Built a GenAI taxonomy pipeline with GPT 4o, achieving 80-95% accuracy in extracting apparel attributes. - Developed a PLM style mapping tool that filtered ~40% of non-matching catalog styles.

Machine Learning Engineer at Paytm, Sep 2022 - Nov 2024 · 2 yrs 3 mos, Bengaluru, Karnataka, India, At Paytm, I developed real-time fraud detection models that achieved over 93% AUC, leading to a 60% reduction in fraud incidents. I optimized credit risk and loan collections using XGBoost and Random Forest, which improved collections by 30%. My work also involved creating recommendation and propensity models that reduced manual effort by 70% and increased profitability by 25%. Additionally, I implemented anomaly detection systems to block suspicious transactions instantly. Achievements: - Built real-time fraud detection models with >93% AUC, reducing fraud by 60%. - Optimized credit risk and loan collections, improving collections by 30%. - Developed recommendation models that cut manual effort by 70% and boosted profitability by 25%.

Software Engineer at Mindtree, Mar 2021 - Oct 2022 · 1 yr 8 mos, Bengaluru, Karnataka, India, As a Machine Learning Engineer at Mindtree, I architected an ML platform using Flask and MongoDB for seamless deployment of machine learning models. I built NLP issue assigners and Xpath reviewers utilizing BERT and XGBoost, streamlining model monitoring and lifecycle management. My role also involved integrating ML solutions efficiently with production pipelines, ensuring robust performance and reliability. Achievements: - Architected an ML platform for seamless deployment using Flask and MongoDB. - Built NLP issue assigners and Xpath reviewers with BERT/XGBoost. - Streamlined model monitoring and lifecycle management for improved efficiency.

Senior Development Associate II at NTT DATA Services, Aug 2019 - Mar 2021 · 1 yr 8 mos, Bengaluru, Karnataka, India, In my role as a Senior Development Associate at NTT DATA, I automated customer review scraping and analysis using Python and Selenium. I built pipelines to extract actionable insights from unstructured data, which significantly improved reporting accuracy and BI turnaround time. Additionally, I supported various machine learning initiatives through feature engineering and ensuring clean datasets for analysis. Achievements: - Automated customer review scraping and analysis with Python/Selenium. - Built pipelines for extracting actionable insights from unstructured data. - Improved reporting accuracy and BI turnaround time significantly.

Education

Bachelor of Technology, Computer Science, CMR Technical Campus (Autonomous Engineering College)