data science

1. Jisu Behera
Data Science Manager
jisu.behera2021@gmail.com +91-7447483228 Pune, India
Linkedin: www.linkedin.com/in/jisu-behera-6bba1521
 15+ years experienced, meticulous & result-oriented Data science manager armed with a proven
track record of analytical acumen in deploying complex machine learning and statistical modeling
algorithms/techniques for identifying patterns and extracting valuable insights. Possesses diverse
experience in planning & executing multiple projects and liaising with the key stakeholders to
identify & resolve business problem statement and deliver excellent results.
Key Skill:
 Machine Learning Methodologies • Optimization Techniques • Text Mining • Data Mining & Analytics
 Predictive & Statistical Modeling • Sentiment Analysis • Data Analysis
 Data Visualization • Project Delivery • Predictive Modeling & Analytics • Programming • Process
Improvement • Agile • Team Coordination & Leadership
 Technical Skill: Machine/Deep learning - Python, Pandas, Numpy, PyTorch, Scikit-Learn, Tensor
flow/Keras, NLP, Spacy, Neural Network, ANN, CNN, LSTM, SVM, Random Forest, supervised &
unsupervised ML algorithms, Transformer, Recommendation system, OpenCV, Computer Vision,
Generative AI
 Data Mining and Analytics skills – Power BI, SAS
 Domain - Credit Card, Credit risk, Fraud prevention , Collection
 Other - IBM Mainframe, COBOL, JCL
WORK EXPERIENCE
Credit risk Model monitoring system - Data Science Manager
January 2020 – current HCL, Technology LTD
We want to ensure that the model can still accurately forecast defaulters based on new
customer data, because the population makeup may change over time.
 Building the Credit Risk model using machine learning
 Extracts data, conducts exploratory data analysis, and addresses common data issues like missing
and extreme values.
 Develops predictive models/scorecards/segmentations that predict customer behavior such as
delinquency, write-off, payment rate, revolve rate, profitability, etc
 Provides support for implementation of models, including monitoring when applicable
 Provides recommendations/insights regarding how to use models
 Supports partners by providing forecasting assistance when needed
 Provides analytical enhancement (i.e., uses advanced tools to enhance analyses)
 Used random forest models to study risk champion/challenger strategies in order to optimize
and increase efficiency of business scenario by 22%

2. Fraud Detection Using Neural Network Classifiers –Data scientist
April 2018 - January 2020 Attra InfoTech
The goal of this project is to design a credit card fraud detection algorithm. This has
been divided into the following two sub-goals: 1. creating a well-functioning credit card
fraud detection system using a neural network classifier. 2. Designing different
generative models to generate synthetic data of the minority class in a heavily
imbalanced dataset and assessing the effects of the models on the classifier.
 Worked closely with the product team to build a fraud prediction engine using deep learning, which
reduced loss by 16%.
 Oversee and contribute to the development and implementation of effective Fraud Management
strategies, Fraud engine score model, balancing the need to reduce our fraud losses, provide
world class customer experience and grow the business.
 Lead initiatives to secure new fraud risk tools/solutions (Scoping, Business Case approval, project
life cycle). Participate in both long and short term projects as assigned with responsibilities
including data gathering, analysis, interpretation and presentation of results, including
recommendations.
 My responsibilities include building models and getting insights from data using Python, SAS.
 Development and application of machine learning algorithms to detect and prevent credit card
frauds AND building fraud detection models using XGBoost and Deep Learning algorithms.
MasterCard – Product Owner
August 2017 - March 2018 ITC InfoTech
 Requirement gathering, backlog maintaining and running sprints as per agile processes for card
issuing system(Account onboarding till transaction processing, Complete card life cycle)
 Defining Scope of Product-I work with key project stakeholders to formulate and communicate the
business vision, to envision initial requirements, and to scope the project/Product and fundamental
goal is to get the project focused early by translating the initial high-level vision into something
realistic
 Translate Business Needs-I work with project stakeholders to translate their requirements into
something that developers can understand as well as to translate the resulting questions that the
developers have into something the stakeholders can understand. This is an iterative process
throughout the project.
 Responsible for creating and managing the product backlog.
 To understand the market, describe product functionality, and prepare for the product launch.
 Responsible for product demonstration to clients and prospects.
 Responsible for product validation and documentation
 Attend product demos, provide product acceptance
 To own and manage the project on behalf of the stakeholders.
HSBC – Business Analyst
August 2008 – August 2017 Capgemini India PVT LTD
 Perform business rule/Configuration changes as per business requirements in PCTMS and blaze
advisor.
 Build credit risk score models using blaze Advisor tools and enhanced the score model as per market
trend/requirement and incorporate information into model inputs.

3.  Perform auto testing in order to verify the changes made to the decision system TRIAD have been
built successfully-This auto testing achieved by developing SAS programs which aim to simulate what
the updated decision system is expected to produce and another one is comparing mainframe batch
output data with SAS simulated outpout data.
 Manage BAU change request starting from Estimation, incident ticket tracking, Development of
strategies, SAS build/Testing in SAS, Build predictive scorecard model and mainframe technical team
for deployment, Business validation after deployment.
 Create RFI/RFP document based on current TRIAD 8.1 system design and present the current
functionality of TRIAD 8.1 to senior management to deicide future migration plan/RFI proposal.
 Review business test cases and help to create test cases as per business requirement.
 Analyzing credit risk, collection, fraud data and proposing solutions to business strategic planning
problems on a one-time or periodic basis to build business rules thru champion /challenger method.
 Providing data-driven decision support.
EDUCATION
BPUT, University – Electrical Engineering
July 2003- April 2007 BBSR,Orissa
SKILLS
Python (NumPy, Pandas, Scikit-learn, Keras, Tensor flow), Machine Learning methodology, Deep
learning(CNN,RNN,LSTM,NLP-NLTK,Spacy), Transformer, ; Leadership Experience-:Credit risk and
FRAUD Application; Recommendation Engines-:Credit card Customer Segmentation, Risk score
modeling, Fraud score engine