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shrjeel imtiaz

DATA SCIENTIST | MACHINE LEARNING ENGINEER

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Intro
Irvine, CA, United States
Sr. Data Scientist / AI/ML Engineer at Meijer
Studied Data Science at University of East London
Information Technology & Services
Joined January 21, 2025
About
As a seasoned Data Scientist with over ten years of experience, I have honed my skills through a diverse range of roles and industries. Beginning as an ML/AI domain experience from 2008 with overall 16 Years of experience and 11+ Years of AI/ML domain experience, I have progressed to Lead and Principal, gaining valuable insights into the development and deployment of complex AI models. Extensive experience in developing and deploying machine learning models and AI applications. Proficient in Natural Language Processing (NLP), Lang chain, and Large Language Models (LLMs). Demonstrated ability in end-to-end machine learning processes, cloud deployment, and AI robustness testing. Strong interpersonal communication skills with a proven record of working effectively in diverse team environments. Principle Data Scientist at Wipro specializing in Anomaly Detection and RCA, Supply Chain Forecasting, Ad Track, Sales Forecasting, Credit Scoring, NLP RAG Services, demand forecasting, Elasticity and Demography analysis. My expertise lies in the analysis of high-volume datasets and the design and development of efficient AI models using advanced deep learning LLM (GPT log, GPT-Turbo, GPT3.5), RAG and DOCAI machine learning algorithms. I have solid experience of group forecasting, LLM bots, elasticity analysis and budget optimization strategies using ML. Utilized Linux scripting for system administration tasks such as server monitoring, process management, and file handling to streamline machine learning infrastructure operations. Integrated Python with big data tools like Spark and Hadoop to handle large-scale data processing and distributed machine learning model training. Utilized Python for exploratory data analysis (EDA) and visualization using Matplotlib, Seaborn, and Plotly, providing actionable insights from complex datasets. My industry experience Logist.ics, Finance, supply chain, consumers, retail and Sales. Throughout my career, I have mentored and guided team members in the implementation and execution of machine learning models at different levels of the project life cycle.
Experience
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Meijer
Oct 2024 – Present
Remote
Sr. Data Scientist / AI/ML Engineer
Designed and implemented an advanced attribution model to forecast sales and compute campaign effectiveness across offsite/onsite attributes, such as NetImpressions, Net Click, Add to Cart, and Web Session points. Enhanced Return on Ad Spend (ROAS) by 1% through data-driven insights. Developed a phantom inventory detection model at the store level, leveraging multi-model techniques to identify discrepancies and optimize inventory management. Integrated ML pipelines with MLFlow, enabling streamlined development and deployment processes for machine learning models on Azure Cloud. Utilized Databricks, Python, and PySpark to process large datasets and develop scalable, efficient data science solutions. Led the development of a predictive analytics solution to optimize product recommendations based on customer browsing and purchasing behaviors, increasing conversion rates by 5%. Conducted A/B testing to measure and analyze the impact of marketing campaigns, leveraging statistical methods to derive actionable insights for marketing teams. Collaborated with cross-functional teams to improve data infrastructure, ensuring high-quality, accessible data for model development and reporting. Applied machine learning algorithms, including decision trees, random forests, and gradient boosting, to develop robust predictive models for customer behavior and inventory forecasting. Developed automated reporting tools in Python and Tableau to visualize key performance indicators and enable stakeholders to make data-driven decisions. Optimized model performance by conducting hyperparameter tuning and feature engineering, improving prediction accuracy by 15%. Environment: Python, PySpark, Databricks, Azure Cloud, MLFlow Pipeline Integration, A/B Testing, Tableau, Random Forests, Gradient Boosting
Education
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University of East London
– Jul 2022
PHD , Data Science