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Data Driven Decisions

Anirudh Mittal

Data Analysis Machine Learning Storytelling & Dashboarding Credit Risk

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About Me

Using data in discovering the unknown unknowns

Profile Picture

I work on breaking complicated business problems in to simple components and applying advanced analytics to solve them.
A graduate of the MS in Business Analytics program from Carlson School of Management which is considered amongst the top 5 courses of Business Analytics in the USA. Have undertaken projects in Dashboarding, Causal Analytics, Machine Learning, Root Cause Analysis, Statistical Analysis, Credit Risk Analytics, Data Validation and Big Data.

Tools:
SQL, SAS, R, Python, Tableau, PowerBI, Excel VBA, Spark, AWS, GCP, Provenir, Connect+

Techniques:
Predictive Modeling, Exploratory Analysis, Statistical Analysis, Time Series Forecasting, A/B testing, Data Visualization, Big Data, Deployment Testing,
Scrum & Agile methodologies, Credit Risk Modeling, Data Validation

Profile

  • Full Name: Anirudh Anil Mittal
  • Job: Data Analyst / Business Intelligence Analyst
  • Email: mitta098@umn.edu

Skills

  • SQL, SAS
  • Python, R, Pandas
  • Hadoop, Spark, AWS
  • Tableau, PowerBI
  • Credit Risk, Finance
  • Project Management
Additional Info


Services

What do I have to offer?

I optimize processes using data

Experienced in analyzing large sets of data to design and develop data systems and reporting tools to ensure that the business and clients team members have the product, support, and operations data they need to make crucial business decisions. I have also had the opportunity to design innovative data solutions and solve challenging problems while deploying a Credit Decisioning tool as part of the Future State Architecture of HSBC Bank.

10000

hours of education

12

Data Science Projects

19

Dashboards Created

22

Tool & Techniques known

4

Years of Experience

6200

Cups of Coffee
Portfolio

What have I been up to lately?

Look here for a collection of my latests projects, articles, and more.

Img via Pixabay

Battleship using Python

Battleship is a guessing game for two players. It is played on
ruled grids on which the players' fleets of ships are placed.
The locations of the fleet are concealed from the other player.
Players alternate turns calling `shots' at the other player's ships,
and the objective of the game is to destroy the opposing player's fleet.
Img via Pixabay

Advanced Machine Learning

Automated running of multiple Machine learning algorithms and compare their performance in predicting cancer.
Img via Pixabay

Storytelling and Visualizations

Have worked on making interactive visualisations for client.
Experienced in working on identifying patterns in data and use them to unearth the unknown unknowns of the data generation process.
Img via Pixabay

Articles

Latest article written by me
Img via Pixabay

Community Service

I believe in constantly giving back to the community in whichever way possible. I aim to play my part in tackling world hunger and poverty by helping in the education of underprivileged children.
Image via Pixabay

Find me on GitHub

My repositories
Resume

More of my credentials.

Currently working as a Credit Risk Analyst and Data Modeler at T-Mobile.

Download Resume

Work Experience

Credit Risk Analyst - TFB Strategy

October 2020 - Present

TMobile - Seattle

Data Modelling and Credit Risk Analytics– (Strategy Development, SQL, SAS, ML,XML Analysis,Data Engineering )
• Created an automated framework on Python which Iterated over 700 Decision tree, Logistic Regression and Random Forest models using data provided by 5 biggest bureaus to determine T-Mobile's new credit bureau partner
• Parsed and analyzed XMLs from all 5 major bureaus involving over 4K variables saving almost 200 hrs of work and enabling TMobile to create new strategies for customers with little to no credit information.
• Created modelling strategy for non-scorable customers(little to no credit data) using decision tree modelling. New strategy resulted in $2 million additional revenue for TMobile .

Data Analyst - Student Consultant

July 2019 - May 2020

Carlson Analytics Lab

Causal Inference in Marketing (SQL, R, Tableau)
Client: Company in Hospitality Industry
• Causal Analysis to show change in onsite headcount, due to customer presence on newly launched mobile app.
• Analyzed 18 years of data to provide insights on past marketing campaigns using SQL and R.
• Provided an A/B testing framework to access the impact of various marketing coupons.
• Created dashboard using Tableau aimed at detecting and visualizing KPIs for business strategy development.

Root Cause Analysis (SQL, R, Tableau)
[Competition Winner]
Case Client: Company in Entertainment Industry
• Combined clustering and association rules algorithms to provide customer level recommendations on when and how to target dormant customers. Also created a workflow to analyze the success rate of each offered coupon.
• Developed a data-driven strategy to improve customer headcount by 11%, through better understanding customer churn cycle and defining customer dormancy thresholds using R and Tableau.

Visualization Dashboard (SQL, Python, Tableau)
[Competition Winner]
Case Client: Mall of America (MOA) Minneapolis
• Determined statistical trends in call frequency combined with exploratory data analysis of 40k+ call log data on Python.
• Created a visualization dashboard on Tableau showcasing slices of data through heat maps; assisted MOA to utilize call log data in day-to-day operations by observing changes in KPI’s.

Credit Risk Analyst - Information Management Risk

February 2016 - May 2018

HSBC Bank, India

Data validation and Customer Insight Generation (SAS, SQL, Excel VBA, MS PowerPoint)
• Analyzed over 15 years of data of all credit products on SAS and SQL aimed at anomaly detection on historically transmitted bureau data; led to the discovery of 12 major errors across reporting systems; increased accuracy of data by over 20%.
• Discovered trends in customer complains and conducted workshops in Dubai for heads of retail banking to acknowledge the bottlenecks in the change management process. Subsequent actions reduced turnaround time by 33%.
• Created an automated solution for tracking customer complaints, using Excel VBA, integrated live visualization dashboard to showcase updates to the stakeholders of HSBC MENA; tool deployed in 4 MENA countries.

Assistant Manager – Future State Data Architecture

March 2018 - May 2019

HSBC Bank, India

Process Optimization and Credit Risk Analytics (SAS, SQL, Provenir, Connect+, Jira, Confluence, MS Visio)
• Collaborated with vendors to deploy a tool in the future state architecture of HSBC, revamping loan decisioning workflow.
• Created and maintained dashboards to track and analyze KPI’s of the Credit decisioning process.
• Led a cross-functional team in coding and testing over 250 new variables to be used in decision making for new loans and credit card offerings; Completed project before time, saving 25% of the resources.

Education

Carlson School of Management, University of Minnesota

June 2019 - May 2020

Masters of Business Analytics

The Carlson School's Master of Science in Business Analytics (MSBA) teaches students how to extract insights with creative data analysis, and then apply the results in real business settings. Students graduate with a unique combination of data science skills and business acumen to lead in an increasingly data-driven world.

Data Science & Analytics Courses:
* Statistics for Data Scientists
* Exploratory Data Analytics and Visualization
* Predictive Analytics
* Advanced Issues in Business Analytics
* Causal Inference via Econometrics and Experimentation
* Modeling and Heuristics for Decision Making and Support

Technical Courses:
* Programming for Data Science
* Data Management, Databases, and Data Warehousing
* Big Data Analytics

Business/Management Courses:
* Agile Management of Analytics Projects
* Building and Managing Teams
* Analytics for Competitive Advantage
* Financial Accounting
* Marketing Management

Manipal Institute of Technology

August 2012 - June 2016

Bachelors in Science, Mechatronics Engineering

Mechatronics as a branch, it is a field of engineering that focuses on the design and production of automated equipment. It is a combination of mechanical engineering, computer control, information technology, and electrical engineering with focus on parts like Programmable Logic Control/ Microprocessors,Electrical Drives, Machine Elements and CAD design etc. Students are taught to apply analytical skills and modelling methodologies to recognize, analyse, synthesize and implement operational solutions to engineering problems, product design and development, and manufacturing.

* Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

* Identify, formulate, research literature, and analyse complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.

* Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.

Where to find me

Seattle, WA
98121 USA

Email Me At
 (mitta098@umn.edu)

Call Me At

Phone: (612) 295-1942