Nitesh Yadav

Operations Associate

Jaunpur, Uttar Pradesh, India3 yrs 9 mos experience

Highly Stable

Key Highlights

Developed automated dashboards for global clients.
Engineered ETL pipelines reducing workload by 40%.
Delivered reports leading to $5.9M in savings.

Stackforce AI infers this person is a Data Analyst specializing in Business Intelligence and Data Visualization within the SaaS industry.

Contact

Skills

Core Skills

Data AnalysisBusiness Intelligence (bi)

Other Skills

DAXDAX (Data analysis expression)Dashboard BuildingDat cleaning and PreprocessingData CleaningData ModelingData VisualizationData-driven Decision MakingETLExcelExtract, Transform, Load (ETL)Machine Learning (basic)Microsoft ExcelMicrosoft Power BIPower Automate

About

With a Bachelor of Technology from NIT Silchar, my analytical journey has led to a Data Analyst role at Wipro, where we've empowered global clients through customized data visualizations and dashboard development. Our team's efforts in automating processes have significantly increased efficiency, leveraging SQL, Power Automate, and Advanced Excel. At Wipro, we've enhanced operational effectiveness for a leading denim brand and a major U.S. nonprofit health plan, delivering financial and operational insights. Looking forward, I'm keen to delve deeper into advanced analytics and machine learning, driving innovation and data-driven solutions that fuel strategic growth.

Experience

Flipkart

Assistant Manager

Aug 2025 – Present · 8 mos

Data AnalysisSQLPythonPower BITableauDAX+5

Wipro

Data Analyst

Jul 2022 – Aug 2025 · 3 yrs 1 mo · Greater noida · On-site

Data Analyst | Wipro
2022 – Present
1.Developed and deployed end-to-end Power BI and Tableau dashboards using complex DAX, calculated fields, and data blending, supporting strategic decision-making across global client accounts.
2.Performed in-depth analysis on sales and supply chain data for a leading denim brand using advanced SQL (CTEs, window functions, joins) to identify patterns in fulfillment rate, rejection rate, and return trends, contributing to a 10% reduction in product rejections.
3.Engineered automated ETL pipelines using SQL Server, Python (Pandas, NumPy), and Power Automate to streamline ingestion of Excel/CSV/JSON data, reducing manual workload by 40%.
4.Delivered automated financial and performance reports for a U.S. nonprofit health plan, integrating Python scripts for data cleaning, validation, and forecasting, which led to $5.9M in annual savings.
5.Designed KPI and SLA monitoring dashboards with dynamic filters and RLS (Row-Level Security) to support business reviews and SLA compliance tracking.
6.Created reusable SQL queries and Python modules for customer segmentation, trend analysis, and monthly churn prediction, improving insight generation speed.
7.Collaborated with business stakeholders, data engineering, and product teams to translate ambiguous business requirements into scalable data solutions using Python, SQL, and BI tools.
8.Conducted root cause analyses and ad hoc investigations using SQL, Excel Pivot Tables, and Python visualizations (Matplotlib, Seaborn) to support strategic planning.