Devambatla Sharanya

Strategic Financial Analyst with 5+ years of hands-on experience spanning healthcare cost analytics, telecom revenue forecasting, and enterprise risk & regulatory reporting, currently driving risk modeling and compliance initiatives at Goldman Sachs. Previously delivered data-driven revenue and ARPU insights at Reliance Industries Limited and optimized medical cost strategies at Accenture (client: Cigna). Combines strong financial acumen with advanced analytics (Python, SQL, R) and visualization tools (Power BI, Tableau) to translate complex data into actionable business insights, enabling forecasting accuracy, risk mitigation, and strategic decision-making.

Financial Analyst – Enterprise Risk & Regulatory Reporting - Goldman Sachs - Ohio (Remote)

(2025-01)

• Develop enterprise risk forecasting models using Python (pandas, NumPy) to simulate credit and market risk scenarios, improving risk prediction accuracy by 18% across portfolios.
• Design interactive risk and compliance dashboards in Power BI to monitor key risk indicators (KRIs), reducing manual reporting effort by 30%.
• Build regulatory reporting datasets using SQL (CTEs, window functions, complex joins) to support Basel III and CCAR requirements, ensuring high data accuracy and audit readiness.
• Automate data ingestion and transformation pipelines using Apache NiFi, streamlining multi-source financial data integration and reducing processing time by 25%.
• Perform statistical risk analysis using R (time-series forecasting, regression models) to identify trends in credit exposure and support proactive risk mitigation.
• Implement data quality validation and reconciliation processes using Informatica ETL, improving consistency across risk systems and reducing data discrepancies by 20%.
• Conduct scenario analysis and stress testing using Excel (VBA, advanced financial models) to assess the impact of adverse economic conditions on capital adequacy.
• Collaborate with cross-functional teams to deliver executive-level risk insights using Tableau dashboards, enhancing data-driven decision-making and reporting efficiency.

Financial Analyst– Jio Revenue Forecasting & ARPU Analysis - Reliance Industries Limited - Mumbai, India

(2021-05 - 2023-07)

• Built ARPU forecasting models using Python (pandas, NumPy) to analyze subscriber usage patterns, improving revenue forecast accuracy by 18% across prepaid and postpaid segments.
• Designed dynamic revenue projection dashboards in Power BI to track subscriber growth, churn trends, and ARPU fluctuations, enabling leadership to make real-time pricing decisions.
• Performed customer segmentation and cohort analysis using SQL, identifying high-value user groups and improving targeted pricing strategies that increased ARPU by 10% in key segments.
• Developed scenario-based financial models in Microsoft Excel (advanced formulas, Solver) to evaluate pricing strategy changes, supporting optimization of telecom plans and boosting projected revenue by ₹120M annual.
• Conducted statistical trend and time-series analysis using Python (pandas, statsmodels) to predict subscriber churn and revenue volatility, improving forecasting reliability and enabling proactive pricing adjustments during market fluctuations.
• Automated data ingestion and transformation pipelines using Alteryx, reducing manual data processing time by 35% and improving data accuracy for monthly revenue reporting.
• Built interactive financial reports in Tableau to visualize KPIs such as ARPU, CAC, and churn rate, improving stakeholder visibility and reducing reporting turnaround time by 25%.
• Leveraged machine learning models using Scikit-learn (regression models) to identify key drivers of ARPU, enabling data-driven recommendations that improved pricing strategy effectiveness.

Financial Analyst- Medical Cost Trend & Claims Analysis - Accenture - Pune, India

(2018-03 - 2021-04)

End client: Cigna

• Utilized Advanced Excel (Pivot Tables, Power Query) to analyze 1M+ healthcare claims records, identifying cost drivers across inpatient, outpatient, and pharmacy spend.
• Queried and transformed claims data using SQL, enabling efficient extraction from enterprise data warehouses and improving reporting turnaround time.
• Built cost trend and forecasting models in Excel (Forecasting functions, What-if analysis) to support quarterly financial planning and budgeting cycles.
• Developed KPI dashboards using Power BI to track medical cost per member (PMPM), utilization rates, and claim frequency for business stakeholders.
• Performed variance analysis using SAP FICO, comparing actual vs budgeted medical costs and highlighting key deviations impacting financial performance.
• Conducted trend and pattern analysis using Excel (Statistical functions) to identify high-cost procedures and seasonal utilization patterns.
• Automated recurring financial reports using VBA, reducing manual effort and improving consistency in monthly reporting deliverables.
• Collaborated with cross-functional teams and presented insights using PowerPoint, supporting decision-making on cost optimization initiatives.
• Validated and reconciled claims and financial data using Alteryx, ensuring data accuracy across multiple reporting sources.
• Supported cost optimization initiatives by analyzing inefficiencies using Tableau dashboards, contributing to measurable reductions in unnecessary healthcare spend.

Master of Science - Business Analytics - Kent State University (2023-08 - 2024-12)

Master of Commerce - Financial Accounting - Kakatiya University (2016-07 - 2018-04)

Bachelor of Commerce - Commerce - Kakatiya University (2013-06 - 2016-05)