Analytics & Engineering Foundations

Early Career · Multiple Organizations

2015 – 2021

Overview

Early career roles across diverse industries including insurance, pharmaceuticals, and software development. These foundational experiences built expertise in analytics, statistics, and software quality assurance, establishing the technical and professional skills that would later enable specialization in data science and cloud engineering.

Each role contributed unique perspectives on data analysis, quality assurance, and technical problem-solving, creating a well-rounded foundation for advanced work in machine learning and cloud infrastructure.

Roles & Responsibilities

Data Analyst · iPipeline

June 2020 – July 2021 · Bromley, Surrey

Analyzed insurance industry data to identify trends, support business decisions, and improve operational processes. Worked with large datasets, created reports and dashboards, and collaborated with cross-functional teams to deliver data-driven insights.

  • Data analysis and reporting for insurance products
  • SQL query development and database management
  • Dashboard creation and data visualization
  • Collaboration with business stakeholders

Clinical Statistician and Data Scientist · GlaxoSmithKline

September 2018 – August 2019 · Uxbridge, Middlesex

Applied statistical methods to clinical trial data, supporting pharmaceutical research and regulatory submissions. Developed expertise in statistical analysis, experimental design, and regulatory compliance requirements.

  • Statistical analysis of clinical trial data
  • Experimental design and methodology development
  • Regulatory documentation and reporting
  • Collaboration with clinical research teams

Software Tester · TCP Lifesystems

June 2015 – August 2018 (Part-Time) · Bromley, Surrey

Ensured software quality through comprehensive testing procedures, bug identification, and quality assurance processes. This role developed foundational skills in software engineering, test automation, and quality management systems.

  • Manual and automated software testing
  • Bug tracking and defect management
  • Test case development and execution
  • Quality assurance process improvement

Skills Developed

Analytics

  • • Data analysis and interpretation
  • • Statistical methods
  • • Reporting and visualization
  • • Business intelligence

Statistics

  • • Experimental design
  • • Hypothesis testing
  • • Regression analysis
  • • Clinical statistics

Software Quality

  • • Test planning and execution
  • • Quality assurance
  • • Bug tracking
  • • Process improvement

Technologies & Tools

SQL R Python Excel SAS Testing Tools JIRA

Foundation for Future Growth

These early career experiences across insurance, pharmaceuticals, and software development provided diverse perspectives on data analysis, quality assurance, and technical problem-solving. The combination of statistical rigor from pharmaceutical research, analytical skills from insurance data analysis, and quality focus from software testing created a strong foundation for advanced work in machine learning and cloud engineering.

The cross-industry experience developed adaptability, communication skills, and the ability to translate technical concepts for diverse audiences—skills that continue to be valuable in consulting and client-facing roles.

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