About
Highly analytical and results-oriented Data Intelligence professional with a Master's in Analytics and Management from London Business School and a Bachelor's in Mechanical Engineering from IIT Bombay. Proven ability to leverage advanced data analytics, business intelligence tools (Power BI, Tableau), and programming languages (Python, SQL) to drive strategic insights, optimize operations, and enhance reporting efficiency. Adept at developing robust data pipelines, designing impactful dashboards, conducting in-depth root cause analysis, and leading cross-functional initiatives to deliver measurable business impact. Seeking to apply expertise in data-driven decision-making to complex business challenges.
Work
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Summary
Driving data-driven insights and operational efficiency for employee mobility trends through advanced analytics, dashboard development, and process automation.
Highlights
Leveraged PostgreSQL and Python to query and aggregate over 200K employee mobility data points across EBRD divisions and geographies, enabling comprehensive monthly deep-dive analysis on movement patterns.
Designed and implemented 4 Power BI dashboards for key employee mobility KPIs, enhancing leadership access to critical workforce insights by 60%.
Automated data pipelines for employee mobility tracking and KPI refreshes using Python scripts and SQL views, reducing analyst reporting time by over 40 hours per month.
Developed 5 distinct segmentation frameworks leveraging demographic, role-based, and historical mobility data to optimize resource allocation strategies across 5 key areas.
Led over 10 stakeholder working sessions to define and validate employee mobility KPI calculations, ensuring cross-departmental reporting alignment across HR, Operations, and Strategy.
Integrated 3 distinct reporting platforms (SSRS, Excel Power Queries, Tableau) to streamline delivery of over 20 complex reports.
Conducted cohort analysis on over 10K employee mobility records, providing measurable insights to support internal HR initiatives and talent development programs.
Developed 15+ KPI scorecards and 5 benchmarking models in Excel and Power BI, facilitating data-driven reporting with detailed regional and division-specific variance breakdowns.
Collaborated with data engineering to ensure schema consistency and validate data integrity across 3 reporting environments (Snowflake, BigQuery, SQL).
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Summary
Developed robust data analytics solutions for enterprise risk and performance reporting, enhancing fraud surveillance and optimizing reporting workflows.
Highlights
Processed and analyzed over 10 million daily transaction records using SQL and Python, establishing a real-time insights layer for daily fraud surveillance across 5 markets.
Developed and deployed 6 interactive Tableau dashboards to track fraud trends, alert categories, and escalation paths, reducing high-risk case triage turnaround by 45%.
Designed and normalized fact and dimension tables for Power BI reporting, improving data load times by 30% and enabling seamless visual drill-downs for stakeholders.
Utilized DAX and Power Query to create calculated columns and KPIs for weekly dashboards, supporting compliance, operations, and finance teams.
Conducted root cause analysis on over 50,000 flagged transactions, identifying recurring false positive patterns and reducing monitoring workflow error rates by 18%.
Developed alert prioritization logic and performance scoring metrics, enhancing alignment between analytics and regulatory reporting standards across 3 regions.
Automated daily reporting workflows via SQL and Python (Pandas) batch scheduling, saving the team 3-4 hours daily and eliminating manual aggregation errors.
Collaborated with 4 departments to enforce data governance rules, validate KPIs, and establish standardized schema and metric dictionaries for all BI tools.
Provided rapid support for stakeholder data requests through ad hoc queries, pivot-based summaries, and executive reports, improving insight delivery speed by 50%.
Education
Awards
Merit Scholarship Awardee
Awarded By
London Business School
Awarded for academic excellence upon admission to the Masters in Analytics and Management program.
Languages
English
Native
Skills
Languages/Tools
SQL, Python, Pandas, NumPy, Scikit-learn, Seaborn, Excel, Power Query, VBA, Tableau, Power BI, Snowflake, BigQuery.
Data Analysis
Statistical Testing, Regression, Forecasting, Time-series Analysis, Clustering, Classification, Cohort Analysis, Root Cause Analysis.
Data Automation
ETL Development, Data Cleaning, Workflow Automation, Batch Processing, SQL Scripting, Data Pipelines.
Presentation & Reporting
Dashboard Development, KPI Reporting, Data Storytelling, Interactive Charts, Drill-down Analytics, Executive Summaries.
Data Governance
Data Validation, Schema Consistency, Documentation Standards, Metric Consistency Checks, Governance Rules.
Business Acumen
Insight Generation, Operational Efficiency Tracking, Cross-team Support, Stakeholder Management.