Nishanth Sura

Data Analyst

Location: NY Phone: 713-***-**** Email: ad23i0@r.postjobfree.com

SUMMARY

Accumulated around 3 years of professional experience as a Data Analyst, demonstrating proficiency in various domains, including Database Management, Quantitative Analysis (Statistics), Data Mining, Text Mining, Optimization, Data Warehousing & Business Intelligence, Time Series, and reporting.

Exhibited expertise in Python libraries such as Matplotlib, Seaborn, and Plotly to craft compelling data visualizations, producing visually captivating charts and graphs.

Executed data analysis and statistical modeling using Python packages like NumPy, Pandas, and SciPy.

Employed Python scripts to execute advanced data cleansing, integrating regular expressions, custom functions, and statistical techniques to ensure data accuracy and uphold stringent data quality standards.

Demonstrated prowess in developing diverse Statistical, Text Analytics, and Data Mining solutions for various business challenges, accompanied by data visualizations using Python & Tableau. Facilitated the design and development of Data warehouses for Business Intelligence data marts and reporting.

Established and managed data dashboards and reports utilizing Tableau and Power BI, providing real-time visibility of business metrics and KPIs to stakeholders.

Orchestrated the design and maintenance of databases in MySQL, MongoDB, and PostgreSQL, guaranteeing data integrity, fortified security, and optimal performance.

Proficiently engineered end-to-end ETL processes, responsible for extracting data from heterogeneous sources, transforming it into meaningful insights, and loading it into target systems.

Harnessed SQL's querying capabilities to extract pertinent data, execute intricate joins, and apply transformations, enabling comprehensive data analysis.

Automated data loading procedures utilizing SSIS, systematically scheduled package execution, monitored performance, and architected multidimensional and tabular data models for OLAP cubes and data mining, leveraging SQL Server Analysis Services (SSAS).

Demonstrated competence in Agile methodologies, fostering seamless collaboration with cross-functional teams to deliver iterative and impactful data analysis solutions. Played an integral role in Scrum ceremonies, refining user stories, and meticulously planning sprints to ensure alignment with project objectives.

TECHNICAL SKILLS

Languages : Python, SQL, R

Visualization : Tableau, Power BI, MS Excel (VLOOKUPS, Pivot tables, Macros, VBA)

Big Data/Database : MySQL, MongoDB, PostgreSQL, SSIS, SSAS, ETL

Others : Data Warehousing, Data Visualization, Data Mining and Data Modeling

Platform/Library : NumPy, Pandas, NLTK, Matplotlib, Sklearn, SciPy, Seaborn, Plotly

Methodologies : SDLC, Agile, Waterfall, Scrum, Jira

Operating System : Linux, Windows, Mac

EDUCATION

Stevens Institute of Technology, Hoboken, NJ Dec 2022

Masters in Information Systems

R.V College of Engineering, Bangalore, India Jul 2019

Bachelors in Information Science Engineering

EXPERIENCE

Data Analyst Molina Health Care, NY Feb 2023 - Current

Implemented agile development methodology, facilitating communication between cross-functional teams and serving as a liaison between business users and technical experts, resulting in a 15% increase in project efficiency.

Utilized Python packages like NumPy, Matplotlib, and SciPy to generate graphical capacity planning reports, leading to informed decision-making and a 25% reduction in resource allocation errors.

Conducted in-depth Data Analysis and Data Profiling, leveraging complex SQL queries on various source systems, including SQL Server, to derive valuable insights that drove a 30% improvement in data quality and decision-making accuracy.

Seamlessly integrated SSIS with Python using script tasks, enhancing data analysis capabilities and manipulation techniques, resulting in a 20% reduction in data processing time.

Utilized Pandas libraries in Python to import claims data, enabling various data analysis processes and insights generation, ultimately reducing data preparation time by 35%.

Executed SQL queries for data analysis, modeling, and validation from relational databases, ensuring data accuracy and contributing to data-driven decision-making, resulting in a 20% increase in data-driven initiatives' success rate.

Demonstrated expertise in data cleansing, validation, and transformation, utilizing ETL methodologies to improve data quality and consistency for analysis and reporting purposes, reducing data errors by 25%.

Built and published customized interactive reports and dashboards using Tableau, ensuring accessibility and report scheduling for stakeholders, resulting in a 40% improvement in data accessibility and understanding.

Successfully extracted data from PostgreSQL databases, contributing to the creation of SQL queries, stored procedures, and common table expressions (CTEs) that played a pivotal role in multiple departmental reports, increasing report generation efficiency by 20%.

Engineered complex Tableau reports by employing functionalities like context filters, hierarchies, and LOD expressions, improving report accuracy by 20% and providing deeper insights into data trends.

Created Business metric KPIs (Key Performance Indicators) to evaluate module-specific factors, enhancing performance assessment and enabling a 15% increase in targeted performance improvements.

Data Analyst KPMG, India Mar 2019 – Feb 2021

Demonstrated expertise in Data Analysis, Data Warehousing, Data Migration, Data Cleaning, Statistical Modeling, and SQL programming, actively contributing to a 20% reduction in decision uncertainty.

Leveraged Python's statistical libraries to conduct hypothesis testing, significance testing, and confidence interval estimation, achieving a 95% confidence level in hypothesis testing.

Implemented sophisticated data cleaning pipelines in Python, leading to a 25% reduction in data errors and a 30% increase in data accuracy and consistency.

Utilized R for Data Acquisition and Data Integrity, encompassing Datasets Comparison and Dataset schema checks, reducing data discrepancies by 15% through systematic data schema validation.

Crafted visually engaging charts, graphs, and plots using Matplotlib and Seaborn in Python, improving data comprehension by 25% and resulting in quicker decision-making.

Imported the customer data into Python using Pandas libraries and performed various data analysis - found patterns in data which helped in key decisions for the company.

Played a key role in creating and maintaining database objects (tables, views, procedures, triggers, and functions) using SQL to optimize data management and enhance efficiency.

Implemented ETL methodology to support data extraction, transformations, and loading processes within a complex EDW using Informatica, reducing data processing time by 40% and improving data accuracy by 15%.

Deployed MongoDB's geospatial capabilities to execute spatial queries, providing valuable location-driven insights and increasing location-targeted marketing effectiveness by 10%.

Provided hands-on support to users in creating and modifying worksheets, data visualization dashboards, and Power BI reports, enhancing data analysis capabilities.

Developed Power BI data visualization using Cross tabs, Heat maps, Box and Whisker charts, Scatter Plots, Geographic maps, Pie Charts Bar Charts, and Density charts.

Leveraged MS Excel for data rules spreadsheets and report preparation, including VLOOKUP, HLOOKUPS, pivot tables, Macros, and data points.

Utilized SSAS and SSIS to enhance data analysis capabilities, defining calculated measures, KPIs, perspectives, and processing large data volumes for reporting and analysis.

PROJECTS

Health Insurance Lead Prediction

Planned and Supervised a four-person team in leads classification using Logical regression with the goal of finding potential clients to buy a health insurance policy.

Designed and deployed the classifier using a database of 50k+ clients with 15 attributes to Predict leads with a high accuracy

Visitor Database management system

Designed and deployed from scratch a full-stack application for a visitor management system

Supervised Development of database schema with a PHP frontend on top of a SQL backend

Spam Filter

Formulated and Implemented a spam filter for texts and emails with Natural Language Processing

Planned and Supervised a two-person team in message classification by using TF-IDF statistics on an N-gram model of Normalized, Stemmed, and tokenized data to efficiently increase accuracy

Movie Recommendation System

Programmed the Netflix problem based on user ratings with 5000 movies as training data

Systematized an amalgam of content-based as well as collaborative filtering/recommendation to find top optimal matches resulting in a high accuracy

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