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Shantanil Hazarika
From United Kingdom 05:14 PM (GMT+01:00)
$80/hr or $30,000/yr

Active 1 hour ago


Member since Jun 2026

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Data Scientist

Data Scientist
Available for hire
Years of experience
3+ years
Experience level
Junior
Download Resume / CV

I am a data scientist and analyst with a background that sits somewhere between the deeply technical and the genuinely human side of data work. I have spent the last four years building machine learning models, data pipelines, and analytics systems, but the part I find most meaningful is not the model itself. It is the moment someone looks at an insight and says "I did not know that" and then actually does something about it. I grew up in India, studied engineering, then moved to Belfast to do my MSc in Data Analytics, which was equal parts exciting and terrifying. Building a life in a new country while studying full time taught me how to figure things out independently, stay curious under pressure, and find community in unexpected places. What makes me a bit different is that I genuinely enjoy the messy middle of data work. The fragmented sources, the ambiguous requirements, the stakeholder who cannot quite articulate what they need. Most people want clean problems. I have come to enjoy the ones that are not. I am currently exploring remote opportunities because I want to work with teams and problems that challenge me regardless of geography. I learn fastest when I am slightly out of my depth, which probably explains most of my career choices so far.

Languages

Employment History

Data Scientist Intern at Advanced Manufacturing and Innovation Center 2025 - 2025
• Built and deployed end-to-end ML pipelines in Python to process and analyse 150,000+ machine log records, applying predictive modelling and anomaly detection techniques that reduced data latency by 40% and increased operational efficiency by 15% across 3 production lines. • Designed and deployed Power BI dashboards tracking manufacturing KPIs, translating complex model outputs into clear, actionable insights for non-technical stakeholders, cutting anomaly detection time by 25% and enabling faster data-driven decisions. • Implemented automated data validation and quality frameworks, improving reporting accuracy to 98% and ensuring reliable, production grade data pipelines for downstream ML model consumption. • Automated end-to-end reporting workflows through cross-functional collaboration with engineering and analytics teams, reducing manual effort by 60% and contributing to a reusable library of data science accelerators
Software Engineer (Data) at Siemens 2021 - 2024
• Developed and deployed forecasting models using Python and Java achieving 86% accuracy across complex industrial time-series datasets, collaborating with business stakeholders to translate model outputs into strategic decisions that reduced customer drop-off by 20%. • Architected scalable RESTful APIs and backend data systems supporting 10,000+ daily transactions across 5+ industrial sites, applying software engineering best practices to ensure production-grade reliability and performance, reducing integration time by 30%. • Established CI/ CD-aligned automated testing pipelines using Selenium and JUnit within an Agile framework, reducing defect rates by 30% and shortening release cycles by 20% — embedding MLOps and quality engineering discipline across the delivery lifecycle. • Drove code quality and model performance through rigorous peer reviews and algorithmic optimisation, increasing system reliability by 40% and mentoring junior engineers on data science and software engineering best practices.

Education

Msc in Data Analytics at Queen's University Belfast 2024 - 2025