Clinical Data Analyst - Well diagnostics centre - Toronto, ON
(2023-01)
Conducted end-to-end healthcare market research and quantitative data analysis projects to generate actionable insights for pharmaceutical, biotechnology, and medical device industry clients.
- Analyzed large, complex healthcare datasets, including patient outcomes, utilization trends, clinical data, and market intelligence reports, to identify emerging trends, data gaps, and opportunities for business improvement.
- Developed and maintained SQL queries to extract, clean, validate, and manage multi-dimensional healthcare datasets from various data sources, ensuring accuracy and consistency of analytical outputs.
- Built healthcare market models and performed trend analysis to support strategic decision-making related to product planning, market forecasting, and healthcare service optimization.
- Investigated data quality issues by analyzing data pipelines, source methodologies, and dataset structures; collaborated with technical teams to identify root causes and implement improvements.
- Translated complex healthcare data findings into clear business insights through PowerPoint presentations, dashboards, and analytical reports for internal leadership and external stakeholders.
- Partnered with cross-functional teams, including clinical experts, product managers, data engineers, and business analysts, to define project requirements, improve analytical workflows, and enhance healthcare data solutions.
- Engaged directly with healthcare clients to understand business challenges, gather requirements, present analytical findings, and provide data-driven recommendations aligned with their strategic goals.
- Supported project management activities by coordinating timelines, tracking deliverables, documenting client feedback, and contributing to statements of work and project planning discussions.
- Applied statistical analysis techniques using Python and Excel to automate reporting processes, improve data efficiency, and uncover meaningful patterns within healthcare datasets.
- Developed expertise in healthcare data structures, medical terminology, data dictionaries, and industry methodologies to accurately interpret and communicate insights.
Medical Data Analyst - Max hospitals - Delhi, India
(2020-10 - 2022-12)
Supported healthcare research and analytics projects for pharmaceutical, medical device, and healthcare organizations by analyzing clinical, operational, and market datasets to generate meaningful insights.
- Performed quantitative analysis on large healthcare datasets, including patient demographics, treatment patterns, healthcare utilization trends, and disease management data to identify key market trends and business opportunities.
- Developed and optimized SQL queries to extract, transform, validate, and analyze data from multiple healthcare databases, ensuring accuracy and reliability of analytical reports.
- Conducted healthcare market research studies to evaluate medical device segments, competitor landscape, product performance, and customer needs across different therapeutic areas.
- Investigated data quality issues by reviewing source systems, data pipelines, and data structures; collaborated with data engineering teams to resolve discrepancies and improve data accuracy.
- Created analytical dashboards, reports, and PowerPoint presentations to communicate healthcare insights, trends, and recommendations to internal teams, healthcare clients, and senior management.
- Collaborated with cross-functional teams including clinical researchers, business analysts, product managers, and data teams to support project delivery and enhance healthcare intelligence solutions.
- Participated in client discussions to understand analytical requirements, clarify business objectives, and provide data-driven recommendations to support strategic healthcare decisions.
- Maintained healthcare data dictionaries, documentation, and analytical methodologies to ensure consistent interpretation and application of healthcare datasets.
- Used Excel, SQL, and basic Python programming for data cleaning, automation, statistical analysis, and improving efficiency of recurring reporting processes.
- Assisted project managers in planning project activities, tracking deliverables, coordinating stakeholder communication, and preparing client-ready analytical summaries.
