Farhana Faruqi is a Data Analyst and Engineer with a strong background in data analysis, ETL pipelines, visualization, and cloud computing. She specializes in transforming raw data into actionable insights that drive business decisions, leveraging her expertise in Python, SQL, and modern BI tools. Her experience spans across healthcare, e-commerce, and finance, where she has worked with large-scale datasets, optimized AI models, and developed robust data pipelines.

Currently, Farhana is an AI Training Analyst (freelance) at Outlier, where she fine-tunes and optimizes AI models to solve complex mathematical and analytical challenges. She applies advanced mathematical theories and algorithms to improve machine learning performance and enhance automated workflows. Previously, as a Data Engineer at Nonny Beer (via RIIPEN), she developed ETL pipelines for e-commerce data, ensuring efficient data aggregation and quality control. She also built interactive Power BI dashboards for business intelligence and implemented security measures to protect centralized data. Her technical expertise includes Snowflake, SQL, AWS Lambda, Python, and Power BI.

Farhana has also contributed as a Data Analysis and Visualization Expert at Ehase Inc (via RIIPEN), where she designed dynamic BI dashboard templates and ensured data accuracy in all visualizations and reports. As a Freelance Data Analyst on Upwork, she has delivered data-driven solutions in e-commerce, finance, and healthcare, helping clients develop automated reporting systems, conduct root-cause analysis, and optimize business strategies using insights from large datasets.

Her passion for data analytics and business intelligence is reflected in her impactful projects. She led an analysis of mental health benefits utilization among First Nation community members, identifying service trends and gaps using claims data and SQL queries. She also conducted a study on Chronic Disease Management in British Columbia, applying interrupted time series analysis to assess the impact of a diabetes management initiative. In another project, she built a predictive model for hospital readmission risks, utilizing logistic regression and random forest algorithms to improve prediction accuracy.

Farhana holds a MicroMasters in Analytics from Georgia Institute of Technology, with additional coursework in Statistics at the University of British Columbia and a bachelor's in Mechanical Engineering. She has earned several industry-recognized certifications, including Microsoft Certified: Azure AI Fundamentals, and successfully completed the KPMG Data Analytics Consulting Virtual Internship. In 2024, she placed 3rd out of 1400 applicants in the Data Analyst job competition by the Government of BC at the Ministry of Health, demonstrating her strong analytical skills and domain expertise.

With a passion for leveraging data-driven strategies to optimize decision-making, Farhana continues to explore innovative ways to integrate AI, business intelligence, and cloud technologies to solve real-world problems.

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  Riipen Level UP 🚀

  Vancouver, British Columbia, Canada