Scalable ML Solutions | Predictive Analytics | Python, SQL, AWS | Real-World Data Problems Enthusiast
Executed end-to-end solutions
Achieved on predictive models

MSc Data Science, Northumbria University, UK
I’m a Passionate Data Scientist and AI Engineer with a strong passion for solving real-world problems through data-driven innovation. I hold an MSc in Data Science from Northumbria University, UK, where I specialized in Machine Learning, Cloud Technologies, and Data Engineering.
Over the years, I’ve developed and deployed end-to-end ML solutions, building scalable systems that bridge the gap between raw data and intelligent decision-making. My expertise lies in Python, SQL, AWS, Databricks, and Tableau, which I use to design predictive models, data pipelines, and automated analytics frameworks that deliver measurable impact.
My professional journey has been shaped by hands-on experience in diverse domains and from crime trend forecastingand financial analytics to healthcare data systems, achieving over 95% model accuracy and significantly improving operational efficiency. I take pride in creating systems that are not just technically sound, but also aligned with real business goals.
What drives me most is the story behind the data and transforming complex datasets into clear, visual insights that guide better decisions. I believe great data science blends analytical precision with storytelling clarity, and I’m committed to mastering both.
I’m currently based in Newcastle upon Tyne, UK, and hold a Graduate Visa valid until December 2026, allowing me to work and collaborate within the UK. I’m always open to new opportunities, partnerships, and projects where I can apply my skills to build scalable, ethical, and intelligent data solutions that shape a smarter tomorrow.
My expertise spans Python, SQL, AWS, and Databricks, through which I develop and deploy predictive models, scalable data pipelines, and automated analytics workflows.
I’ve successfully executed end-to-end solutions across domains like crime analysis, healthcare, and financial forecasting, achieving measurable gains in model performance and efficiency.
Specializing in Machine Learning, Data Engineering, and Cloud Technologies to build intelligent systems.
Proficient in AWS and Databricks for scalable ML solutions and data pipeline deployment.
Creating impactful visual narratives with Tableau, Power BI, and interactive dashboards.
Newcastle Upon Tyne, England, United Kingdom
Graduate Visa valid until December 2026
Expertise in developing predictive models and classification systems using advanced ML algorithms.
Specialized in forecasting models for crime trends, claims data, and financial metrics.
Experience in healthcare data systems and hospital management solutions.
Predictive analytics for law enforcement with 85% accuracy improvement.
Healthcare ML model with 92% diagnostic accuracy.
Financial forecasting model with real-time data integration.
Automated risk assessment reducing processing time by 40%.
My expertise spans a wide array of technical domains, driving innovative solutions and efficient data workflows. Here's a breakdown of my core competencies:
Programming
Cloud Platforms
Visualization
ML Frameworks
Data Engineering
Analytics
Specialized in data manipulation, analysis, and model development.
Experience building cloud-integrated data solutions and automated pipelines.
Creating interactive dashboards and executive reports for informed decision-making.
Developing and deploying robust machine learning models.
Designing efficient data integration and transformation workflows.
Extracting key insights from complex datasets to drive strategy.
My commitment to continuous learning ensures I stay at the forefront of technological advancements, consistently delivering high-quality, scalable, and impactful data solutions.
November 2024 - Present | Remote, United Kingdom
As a Data Analyst at Kalanjiam Enterprises, I have been instrumental in driving data-driven decision-making and enhancing operational efficiency for Tata AIG's insurance operations. My work has focused on leveraging advanced analytics, automating data pipelines, and developing comprehensive dashboard reporting to provide actionable insights.
Delivered robust data analytics and forecasting solutions for Tata AIG's Europe and UK insurance operations. My focus included detailed risk analysis, claims forecasting, and uncovering critical customer retention insights to inform strategic initiatives.
Architected and automated Azure Data Factory and Databricks pipelines, seamlessly integrating CRM, policy, and claims data from diverse regional sources. This critical automation significantly improved data availability and reliability for reporting and analytical purposes.
Developed dynamic Power BI dashboards to provide real-time visibility into key insurance metrics. These dashboards track critical indicators such as claims frequency, settlement time, and agent performance, empowering stakeholders with immediate insights.
Designed and deployed Python-based forecasting models for predicting claims trends and optimizing policy renewals. These predictive models are vital in supporting strategic planning, resource allocation, and proactive risk management.
Reduction in manual reporting through centralized data pipelines
Maintained consistency across datasets via robust validation scripts
Accelerated access to critical KPI reports and executive dashboards

Significantly improved data availability for reporting
Architected automated Azure Data Factory pipelines
Uncovered insights leading to improved retention strategies
Data Analyst Intern | July 2025 - August 2025 | London Area, United Kingdom
Streamlined data processes and enhanced reporting capabilities, driving efficiency and informed decision-making across key business functions.
Built centralized data pipeline using Python and SQLAlchemy, integrating multiple sources to cut manual reporting by 50%.
Created and maintained Power BI and Tableau dashboards for marketing, finance, and operations teams.
Assisted in defining key business metrics, ensuring consistency across dashboards and reports.
Supported dashboard testing, report automation, and stakeholder feedback sessions.
Data Science Intern | July 2022 - October 2022 | Hyderabad, India
Leveraged data science methodologies to enhance model accuracy and streamline data processing workflows, significantly contributing to fraud detection and operational efficiency.
Improved fraud detection and forecasting models by 73%, significantly boosting reliability and performance.
Reduced ETL latency by 60% through the implementation of automated pipelines using Databricks and Azure Data Factory.
Developed and delivered impactful Power BI dashboards for critical financial KPIs and claims data, enabling informed decision-making.
Applied stringent data governance practices to ensure robust data integrity and compliance with GDPR regulations.
Improved Model Accuracy
Reduced ETL Latency
Increased Reporting Efficiency
Northumbria University | September 2023 - September 2024
Advanced studies in machine learning, data engineering, and cloud technologies with focus on real-world applications.
NIST University | August 2019 - June 2023
Foundation in computer science, programming, and information systems.
Data visualization and dashboard design expertise.
Proficiency in object-oriented programming fundamentals.
Skills in programming and data analysis using Python.
Mastery in machine learning and advanced analytics.
I transform complex data into strategic assets through innovative machine learning, robust data pipelines, and scalable cloud solutions. My passion lies in delivering actionable insights and impactful results that push boundaries and drive tangible business outcomes.
Ready to build a data-driven future? I am actively seeking full-time opportunities in the United Kingdom for immediate roles focused on data innovation.
Newcastle Upon Tyne, UK

Let's Collaborate
Ready to transform complex datasets into actionable business insights. Available for immediate opportunities across the United Kingdom.
"Where algorithms find meaning in noise"