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    Harshada More e

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    Harshada More
    Harshada More is a junior data scientist with 2.8 years of experience in data science. She has skills in Python, machine learning algorithms, SQL, and AWS. She has work experience building predictive models for loan default prediction and enhancing customer insights. Her projects include a loan predictor system and automating extraction of information from loan documents. She has a computer engineering degree from Savitribai Phule Pune University.

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    Harshada More e

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    Harshada More
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    Harshada More is a junior data scientist with 2.8 years of experience in data science. She has skills in Python, machine learning algorithms, SQL, and AWS. She has work experience building predictive models for loan default prediction and enhancing customer insights. Her projects include a loan predictor system and automating extraction of information from loan documents. She has a computer engineering degree from Savitribai Phule Pune University.

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    Harshada More is a junior data scientist with 2.8 years of experience in data science. She has skills in Python, machine learning algorithms, SQL, and AWS. She has work experience building predictive models for loan default prediction and enhancing customer insights. Her projects include a loan predictor system and automating extraction of information from loan documents. She has a computer engineering degree from Savitribai Phule Pune University.

    Copyright:

    © All Rights Reserved
    Download as PDF, TXT or read online from Scribd
    Download as pdf or txt
    12 views2 pages

    Harshada More e

    Uploaded by

    Harshada More
    Harshada More is a junior data scientist with 2.8 years of experience in data science. She has skills in Python, machine learning algorithms, SQL, and AWS. She has work experience building predictive models for loan default prediction and enhancing customer insights. Her projects include a loan predictor system and automating extraction of information from loan documents. She has a computer engineering degree from Savitribai Phule Pune University.

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    © All Rights Reserved
    Download as PDF, TXT or read online from Scribd
    Download as pdf or txt
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    Contact

    HARSHADA MORE
    Phone 8446490839 Junior Data Scientis t

    Email harshadarajesh2906@gmail.com Data Science Professional with around 2.8 years of functional expertise in preparing data,
    developing and deploying highly scalable machine learning models. Hands-on experience in
    Address Nashik,Maharashtra building and running Machine Learning models in low power edge devices with reputed
    organization.

    Skills WORK EXPERIENCE


    Python/ML packages: ·Scikit Learn, Junior Data Scientist
    Pandas, NumPy, RegEx, Matplotlib, CISIN |Bengaluru |June 2021 - Present
    Seaborn for visualization. Undertook data collection, preprocessing, and analysis.
    Algorithms: Linear Regression, Built models to address business problems.
    Presented information using data visualization techniques.
    Logistic Regression, Naive Bayes
    Identified valuable data sources and automated collection processes.
    Classifier, k-NN, Support Undertook preprocessing of structured and unstructured data.
    VectorMachines, Decision Tree, Analyzed large amounts of information to discover trends and patterns.
    Random Forest, Adaboost, k-mean Built predictive models and machine-learning algorithms.
    cluster. Combined models through ensemble modeling.
    Proposed solutions and strategies to business challenges.
    Web stack: Flask. Collaborated with engineering and product development teams.
    Deep Learning: Neural Networks, Applied machine learning algorithms to analyze and interpret large datasets, resulting in a
    Deep Learning, ANN, CNN, DNN, 15% improvement in predictive modeling accuracy.
    Transfer Learning, Back Developed and implemented data preprocessing pipelines, improving data quality and
    reducing processing time by 20%.
    Propagation, Linear Algebra,
    Activation & loss functions,
    optimizers, TensorFlow 2.x, Keras,
    Database: SQL, MongoDB, 3C PROJECTS
    (Command, Constrains, Clauses),
    CRUD operations, Subqueries,
    Window functions, Joins LoanPredictor Elite System
    AWS: Elastic Compute Cloud, Domain: Finance and Banking
    Sagemaker, Notebook instance,
    The objective of our project is to predict whether a loan will default or not based on
    AWS container, Simple Storage
    objective financial data only and whether investors should lend to a customer or not.
    Services S3, Deployment, Multi Banks and financial institutions face significant challenges in managing their loan portfolios
    cloud environment. and ensuring timely repayment. Loan defaults can result in financial losses for the lenders.
    NLP: Text understanding, Therefore, there is a need to develop a predictive model that can identify potential loan
    representation & classification defaulters early in the lending process. The project utilizes machine learning techniques to
    predict the likelihood of a borrower defaulting on their loan, offering valuable insights to
    techniques, Text clustering skills
    financial institutions for better risk assessment and decision-making.
    Libraries: nltk, spacy, gensim,
    textblob, langdetect, googletrans
    Textual Opinion Analysis: Enhancing Customer Insights
    Maths & Stats: Filter, Wrapper,
    Embedded Method, P-Value, T-Test, Domain: Business Products and Software Service
    Z-Test, ANNOVA test, Chi-Square Enhanced customer sentiment analysis by implementing advanced NLP and machine
    Test, Info-Gain Test, Hypothesis learning models. Applied a root cause analysis layer to identify factors behind sentiments,
    Testing. probability, statistics, linear moving beyond binary classifications. Collected and preprocessed diverse datasets, ensuring
    high-quality inputs. Achieved nuanced understanding and empowered targeted
    algebra, probability, statistics, linear
    improvements, leading to increased customer satisfaction scores and informed decision-
    algebra. making

    Digitalization of Document
    Domain: Finance and Banking

    The Loan Document Extraction project aims to automate the extraction of relevant
    information from loan documents, which often come in various formats and layouts. This
    process is time-consuming and error-prone when done manually. OCR Systems refers to
    managing and accessing the documents electronically. Build a model to automate the
    verification of Loan approval documents extraction
    for a Loan document extraction project, we use OCR (Optical Character Recognition) and
    regex (regular expressions) to automate the extraction of key information.
    TECHNICAL SKILLS Education
    Tools: Git, Jupyter, VS Code Savitribai Phule Pune University
    Languages: Python, SQL
    BE | COMPUTER ENGINEERING | 2021
    Machine Learning: TensorFlow,
    scikit-learn MSBTE, PUNE
    NLP : Text understanding, BOW,
    TFIDF, word2vec ,nltk library HSC | SCIENCE| 2016
    Deployment: Docker Cloud MSBTE, PUNE
    Platforms : AWS, Google Cloud
    Operating Systems: Linux, SSC | 2014
    Windows.

    STRENGTHS PERSONAL DETAILS


    Creative, strong logical and DOB : 06/12/1998
    analytical ability. Gender : Female
    Very strong and effective Marital Status : Unmarried
    organizational skills. Languages : English, Hindi, Marathi
    Keen & Perfectionist and want
    everything to be done right the first
    time.Zeal to get things done on
    time and neverpostpone them.
    Quick Learner
    Commited to life-long learning

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