Data Analyst Business

SANA NIKHAT

+1-630-***-****, ************@*****.***, Chicago IL, 60659.

Career Overview

Results-driven Business Analyst Data Analyst with extensive experience in transforming complex data into actionable insights to drive strategic decision-making and business optimization. Proficient in statistical analysis, predictive modeling, and data visualization using tools such as Python, R, SQL, Tableau, and Power BI. Demonstrated expertise in identifying key trends, streamlining processes, and improving operational efficiencies to support organizational goals. Adept at collaborating with cross-functional teams, ensuring data integrity, and delivering insights that enhance cost management, product development, and market positioning. Proven ability to bridge the gap between data analysis and business strategy to enable innovation, growth, and measurable performance improvements.Passionate about utilizing data to drive innovation, growth, and business performance.

Career Highlights

Business Analyst Intern

Marigold Market.co.in — [2023 -2024]

Chicago, United States.

Gathered and analyzed business requirements to support project objectives.

Conducted data analysis and created reports using Excel, SQL, and Tableau.

Identified process inefficiencies and proposed actionable improvements.

Performed market research and analyzed trends to support strategic decisions.

Created detailed documentation, including process flows and project updates.

Collaborated with cross-functional teams to ensure successful project execution.

Supported User Acceptance Testing (UAT) by validating requirements and outcomes.

Presented findings and insights to stakeholders for informed decision-making.

Data Analyst

Asmoh Laboratories — [2021-2023]

India.

Led comprehensive data analysis projects related to clinical trials, market trends, drug efficacy, and patient demographics, providing actionable insights to senior management and cross-functional teams.

Utilized advanced statistical tools such as R, Python, SAS, and SQL to analyze large datasets, including clinical trial data (Phase I, II, III), sales data, and lab results.

Developed predictive models to forecast market demand, treatment outcomes, and drug adoption, contributing to the strategic decision-making process for new product launches.

Collaborated with R&D teams to support drug development efforts by providing data-driven insights on patient populations, trial results, and regulatory compliance.

Created dynamic dashboards and data visualizations using Tableau and Power BI, ensuring stakeholders at all levels could easily access key insights and track project performance.

Conducted trend and KPI analysis on sales performance, clinical trial progress, and market penetration, identifying key opportunities and risks to inform business strategy.

Worked closely with medical affairs and regulatory teams to ensure data accuracy and compliance with industry standards (e.g., GxP, HIPAA), assisting with the preparation of regulatory reports for agencies such as the FDA and EMA.

Spearheaded data quality assurance processes, conducting regular audits to identify discrepancies and ensure the integrity of clinical and operational data.

Mentored junior data analysts and interns, providing guidance on best practices for data analysis, visualization, and reporting, fostering a collaborative learning environment.

Key Achievements:

Successfully improved the data reporting process, reducing the time needed for ad hoc reports by 30% through automation and improved workflow management.

Played a pivotal role in the launch of a new pharmaceutical product, utilizing market analysis and clinical data to drive key pricing and marketing decisions.

Contributed to the successful FDA approval of a drug by ensuring compliance with regulatory data submission requirements and maintaining high standards of data integrity.

Data Analyst Intern

Yashoda Hospital — [2018-2019]

Hyderabad, India.

Assisted in analyzing patient nutrition data to identify trends and outcomes related to dietary interventions, contributing to improved patient care strategies.

Supported the development of nutrition dashboards using Excel and Tableau, providing healthcare professionals with clear insights into patient dietary needs and progress.

Cleaned, processed, and organized large datasets from hospital nutrition programs, ensuring data integrity and accuracy for reporting and analysis.

Worked closely with dietitians, nutritionists, and healthcare teams to evaluate the effectiveness of dietary programs and interventions, helping improve patient outcomes.

Conducted basic statistical analyses using R and SQL to examine correlations between nutrition intake and patient health metrics (e.g., weight loss, recovery time, etc.).

Contributed to the creation of monthly reports on nutrition-related KPIs (e.g., patient adherence to diet plans, nutrition assessment completion rates, patient feedback on nutrition programs).

Supported efforts to optimize operational efficiency by analyzing patient flow data and recommending improvements in service delivery.

Technical Skills

Data Analysis: R, Python, SAS, SQL, SPSS

Data Visualization: Tableau, Power BI, Excel (Advanced)

Machine Learning: Predictive modeling, Regression analysis, Time-series forecasting

Clinical Data: Medidata, Oracle Clinical, REDCap

Statistical Methods: Hypothesis testing, ANOVA, regression analysis, survival analysis

Database Management: MySQL, Microsoft SQL Server, PostgreSQL

Compliance & Regulations: GxP, 21 CFR Part 11, HIPAA, FDA, EMA guidelines

Education

Masters of Science in Information Technology Management

Indiana Wesleyan University— [2023-2025]

Merrillville, USA

Masters of Science in Computer Science

Osmania University— [2018]

Hyderabad, INDIA

Certifications

Advanced Data Analytics Specialization (Coursera, IBM) — [2024]

Projects

Nutrition Dashboard Development

Designed and developed an interactive dashboard using Tableau to visualize trends in patient dietary adherence, weight changes, and recovery progress, enabling healthcare providers to track patient outcomes in real-time.

Dietary Intervention Effectiveness Analysis

Analysed patient data from a dietary intervention program to assess changes in health metrics (weight, blood pressure, etc.) using R and SQL, identifying key factors that contributed to improved patient outcomes.

Publication

Project Work for research in Prevention and Awareness of Diet in Diabetes Published on Ijracet. Paper ID : IJRACET10739 “Prevention and Awareness of Diet In Diabetes ; Sana Nikhat; Volume 5; Issue X, October 2017”.

Key Competencies

Data-driven Decision Making: Expertise in transforming complex data into strategic insights that drive business and operational decisions.

Cross-functional Collaboration: Proven ability to work effectively with R&D, marketing, regulatory, and medical affairs teams.

Data Integrity & Compliance: Extensive experience ensuring data quality, accuracy, and regulatory compliance.

Advanced Statistical & Analytical Skills: Expertise in statistical modelling, hypothesis testing, and data forecasting.

Problem-Solving & Innovation: Strong analytical and problem-solving skills, consistently identifying opportunities for process improvement.

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