Data Analyst

DHANUNJAI KASUKURTHI

E-mail: *******************@*******.***

Mobile: 91 - 850*******

3+ Years of Experience in Data Science and Analytics across industries with strong technical skillset and business understanding

Domain experience in banking, insurance, manufacturing and retail

Expert knowledge in developing and debugging in Python and R.

End-to-end hands-on experience from prototyping to deployment and production in ML

Expertise in building Regression, Classification, Recommendation and Marketing models

Analytics : Python, R, Java, Unix

Database : SQL(Oracle 12c), SQL Server, MySQL, Mongo

Visualization Tool : Power BI, Tableau, Excel Dashboards

Frameworks : Flask API, Django, Dash, R shiny

IDE : PyCharm, Spyder, Jupyter Notebook, RStudio

Version Control Tools : GIT, SVN,CI/CD

Methods: Predictive Analytics, Econometrics, Regression Techniques, Classification Models, Recommendation Models, Clustering, Price Optimization Models, Deep Learning, Reinforcement Learning, Text Analytics (NLP/NLG), Image Analytics (Computer Vision/OCR/ICR), Acoustic Analytics, Time-Series Models, A/B testing, Agile Model

Algorithms: Logistic Regression, Random Forest, CART, Decision Tree, MLP, LSTM, CNN, RNN, GRU, VAR Time-Series models (ARIMA/ARMA), Holt-winters, Fourier and wavelet transforms, Volatility Models (GARCH), SVM, Naïve bayes, Genetic Algorithm

Packages/Libraries: TensorFlow, Keras, NLTK, Spacy, Genism, Bert, OpenCV, CUDA, NumPy, SciPy, Pandas, Scikit-learn, Matplotlib, Chatterbot

Relevant Knowledge: MLOps, Bigdata Ecosystem (Hadoop, Map Reduce, HBase, Hive, Mahout, Kafka, Oozie, Sqoop, Flumes, Spark, Cloudera, MapR, Unomi, Elasticsearch), ETL, Data warehouse(OLAP/OLTP), HTML, CSS, Java Script, SparkML, SparkSQL, Containerization, Docker, Kubernetes, Orchestration, Jenkins, AWS, Azure, GCP, IOT

May 2019(to date)

Project: Insurance Agency Digital Transformation Domain: Insurance

Project Features: Build a digital platform to perform business operations at one place with master data management and business insights which turns raw business data into powerful insights into the performance of business.

Language: Python, powerBI

Responsible Areas:

For a middle east based Insurance Agency, led end-to-end from presales to development and deployment activities for building single analytics platform to track all business activities

Worked closely with business stake holders to enable multiple levels of analysis on key performance indicators for agency’s book of business, employee operations and insurer relationships

Integrated machine learning based recommendation engine to the existing website to personalize the order of policies

Integrated FAQ chatbot to the existing website

Implemented market mix model for deep understanding of multi-channel target marketing and optimization in direct mail and/or interactive marketing and ROI

Responsible for analytics team of 4 (Team Leader) and guided the business intelligence team to create dashboard on employee insights, Sales Performance, Client retention and Insurer relationships

Project: Balance Sheet automation and comparison using Optical Character Recognition(OCR) Domain: Banking

Project Features: Building a robust engine that can extract, process and store consolidated financial statements from balance sheets in a structured format, which is further fed as input to the in house CompariSense product

Language: Python

Responsible Areas:

Converting pdf to images and perform required image processing techniques

Using tesseract to extract text from the images

Extracting Geometrical data of the detected text’s location

Detecting and extracting required fields by using regular expressions and NLP logics for balance sheet automation

Feeding the structured and processed output to the CompariSense product

Project: Customer Analytics Domain: Banking

Main project features: Customer analytics is insights roadmap to advance segmentation, customer retention marketing strategies, customer wallet share, cross-product propensity and marketing optimization to result in a profitable portfolio

Language: Python, SQL

Activities performed:

Collaborated with cross functional teams (Finance, Marketing, Sales) to understand business context, identify critical business problems and translate them into technical analyses, Spot trends and correlation between business actions and business performance on different customer segments

Understand and leverage data in various forms and channels - including customer transaction data, CRM data, social data and survey data

Understanding and analysing customer behaviour across different touch points in his transactional journey with bank to enhance his lifetime value and decrease his probability of going inactive

Worked along with team to develop Customer Retention/ROI strategies based of his behaviour scores (calculated using statistical approach), Lifetime value, Behavioural Segment, probability of going inactive and product recommendations

Provide statistical support for marketing activities (such as price savings substantiations) to be used across all marketing channels

Collaborated with business intelligence team to maintain and develop regular reporting dashboards to track market performance and key metrics

Project: Credit Risk Scorecard (Application, Behavioral and Fraud) Domain: Banking

Main project features: For a financial institution using rule-based risk analytics we build machine learning based multiple credit scorecards to improve efficiency of credit risk system across the portfolio

Language: R, SQL

Responsible Areas:

Collaborated with SME and data warehouse team to derive the key performance indicators of risk

Build behavioural score card model to reduce Portfolio Default Rates and First Payment Default rates, with improvement in Gini and KS metrics

Worked closely with the team to build application and fraud score cards

Reinforcement learning for recalibration at weekly intervals to continuously improve the accuracy over time

Deployment through Integrating with CRM and transactional/master data to build scorecards

Project: Deriving risk buckets based on propensity of churn Domain: Telecom

Project Overview: To identify customers who have a higher propensity to churn due to bad debt (high risk customers). Develop profiles of low, medium and high-risk customer based on the risk of churn.

Language: R

Responsible Areas:

Performed data cleansing, data manipulation and exploratory data analysis to identify, analyse and interpret data to find out trends/patterns in large data sets using R

Identified factors effecting churn like customer demographics, billing, lifestyle, spends and lead the discussion calls

Performed Data Visualization to analyse outliers

Coordinating with ETL and Business team and analysed other churn models

Applied Clustering and Logistic regression techniques to get through the result

Project: Development and Maintenance of central SQL database Domain: Manufacturing

Responsibilities:

Worked on enhancements and developed modules for new functionalities as SQL Analyst

Maintained and Supported central database of Delphi Automotive Systems(Global Shared Data)

Worked with ServiceNow for incident management and configuration issues and database setup in client machines

Worked in Onsite Offshore model with clients from US, UK and china for requirement gathering and resolving issues

●Bachelor of Technology(CSE) : Gandhi Institute of Technology and Management

●Intermediate : Sri Chaitanya Junior College

●10th Standard(CBSE) : Jawahar Navodaya Vidyalaya

●First project I have worked is transferred from HPE to TCS, I have been the part of knowledge transition of project and gave playback to the client

●Got appreciation from client for an idea I provided which saved the money to client for supporting the application

●Have gained confidence in interacting with the customers

●Have gained exposure to Team handling and customer query handling skills

I hereby declare that the information’s furnished above are true to the best of my knowledge and belief.

PROFILE SUMMARY

TECHNICAL SKILLS

Methods/Techniques

WORK EXPERIENCE

Data Scientist – Lera Technologies Pvt Ltd, India

Data Analyst – Tata Consultancy Services, India

(June 2016 – May 2019)

ACADEMICS

ACHIEVEMENTS

DECLARATION

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