Amal Panwar

Data Scientist

Delhi, India 7+ yrs exp 90 · Outstanding

About

Data Scientist and Analytics professional with 7+ years of experience in machine learning, statistical modelling, AI solutions, and large-scale data analytics, along with a Master’s degree in Data Analytics from the University of Strathclyde. Skilled in Python, SQL, R, Power BI, Azure, and big data technologies, with hands-on experience in predictive analytics, computer vision, RAG pipelines, and time series forecasting. Experienced in building scalable data pipelines, probabilistic models, and AI-driven systems that support data-driven decision-making. Passionate about leveraging advanced analytics and technology to solve complex business and sustainability challenges.

Skills & Expertise (48)

Python Expert

9.5/10

Years Exp

NumPy Expert

9.0/10

Years Exp

Statistical Analysis Expert

9.0/10

Years Exp

Deep Learning Expert

9.0/10

Years Exp

AI Expert

9.0/10

Years Exp

scikit-learn Expert

9.0/10

Years Exp

Pandas Expert

9.0/10

Years Exp

SQL Advanced

8.5/10

Years Exp

Data visualisation Advanced

8.5/10

Years Exp

Microsoft Azure Advanced

8.5/10

Years Exp

Matplotlib Advanced

8.5/10

Years Exp

Visio AB Testing p-value Problem-solving Risk Management Microsoft Office Suite Dynamic 365 Power BI Excel SQL Server Management Studio Jira Guidewire RStudio Teradata Postman Jenkins Git Jupyter SSIS Shiny ggplot2 Java C++ DAX Mathematics Data Mining Agile Methodology VSTS Hypothesis Testing SSRS SSAS YOLO OpenCV RAG LangChain LLM Time Series Analysis

Work Experience

Data Scientist - Quant

Sporting Solutions

Mar 2025 - Mar 2026

Improved NFL odds across multiple markets by analysing bet flow data and customer behaviour, identifying weaknesses in existing models, and refining pricing to reduce client losses. Built ML pipeline in Python and statistical model in R to predict outcomes across sports, improving pricing accuracy and competitive positioning. Developed betting markets using F# and C#, applying statistical methodologies and simulation techniques to model player and team performance. Created and maintained pricing grids for various sports, enabling consistent modelling of probabilities and odds across markets. Conducted distributional and regression analysis and AB Testing of player prop markets, identifying appropriate statistical fits for simulation and pricing.

Data Analyst/Scientist -Sports

Elgin City FC

Jun 2024 - Feb 2025

Leveraged WyScout data and applied machine learning algorithms to identify high-potential player replacements, aiming to significantly enhance team performance. Conducted match analysis using Computer Vision techniques to support post-match evaluations, driving targeted improvements for future games. Created visual comparisons of target players against league benchmarks using gauge charts and radar plots, streamlining the scouting process and improving efficiency. Integrated data from diverse scouting reports to produce visuals that highlight player strengths and weaknesses, contributing to an anticipated 20% improvement in team decision-making. Developed an Agentic AI chatbot using RAG and LangChain to help scouts interact with dashboards and retrieve actionable insights.

Data/Statistical Analyst

Caribbean Goods

May 2023 - Dec 2023

Researched environmental factors affecting coffee sustainability in Brazil, Guatemala, Honduras, and Nicaragua using data mining techniques (KDD) to identify hidden patterns and actionable insights. Analysed macroeconomic indicators to assess their influence on Coffee Future prices. Achieved a mean absolute percentage error of less than 7% in price predictions using statistical and econometric modelling. Leveraged digital transformation and asset management strategies to help farmers optimise resource allocation, resulting in a 25% increase in sustainable coffee growth in tropical regions.

Data Analytics - Consultant

Capgemini

Mar 2022 - Aug 2022

Extract and transform data in Power BI to fulfil a range of requests, creating insightful reports and identifying KPIs that align with business goals. Utilised the Pytest automation framework to validate ETL test cases and reduce 30% testing time.

Junior Data Engineer/Analyst

Cognizant

Nov 2017 - Mar 2022

Spearheaded the development and implementation of a robust data warehouse framework, refining end-to-end data extraction, transformation, and loading (ETL) processes. Leveraged PySpark and Azure Databricks for scalable big data processing, reducing data pipeline execution time by 35% and enhancing analytics capabilities. Utilised T-SQL, MS Excel, and Power BI to uncover valuable insights, detect patterns and identify trends within complex datasets. Executed Data Quality Analysis, identifying anomalies to enhance overall data quality by 20% – 30%. Utilised machine learning modelling techniques in Python to develop a demand forecasting model, leading to a 15% reduction in inventory write-offs. Thrived in collaborative team environments, demonstrating a proactive approach, strong multitasking abilities, and a history of autonomous contributions that significantly elevated data analysis and reporting processes.