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Click here or scroll down to respond to this candidateCandidate's Name
DATA SCIENTISTCharlotte, NC Mobile: PHONE NUMBER AVAILABLE Email: EMAIL AVAILABLE SUMMARY Accomplished data scientist with over 6 years of experience excelling in Python, SQL, R, and MATLAB for diverse data analysis and modeling projects. Proficient in leveraging powerful frameworks and tools such as Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, TensorFlow, and PyTorch for robust data processing and machine learning. Expert in data visualization using Tableau, Power BI, and Advanced Excel, with a strong focus on creating insightful visual representations of complex datasets. Skilled in statistical and machine learning techniques, including NLP, clustering, neural networks, regression, classification models, time series analysis, fraud detection, sentiment analysis, and deep learning. Comprehensive database expertise encompassing MySQL, PostgreSQL, SQL Server, and MongoDB, along with experience in cloud technologies such as AWS and Microsoft Azure. Well-versed in the end-to-end data science process, including ETL processes with tools like SSIS, SSRS, SSAS, and proficiency in Docker, Kubernetes, Informatica, Talend, Amazon Redshift, Snowflake, and Apache Airflow. Demonstrated proficiency in data quality and governance, machine learning algorithms, financial modeling, big data analytics, data mining, and transformation. Participated in regular Technical Reviews, Defect review and walkthrough meetings with important project and business stakeholders throughout the project life cycle. Proficient in version control tools like GitHub and diverse tools such as MS Office, OLAP, and OLTP for effective collaboration. Identified and measured KPIs, recommending improvement strategies across all business areas to enhance overall organizational performance. Offered information, feedback, and guidance to clients, facilitating informed technology-related decision-making, and ensuring strategic alignment with business goals. SKILLSProgramming Language: Python, SQL, R, MATLABFrameworks & Tools: Pandas, NumPy, Matplotlib, Seaborn, Plotly, ggplot2, Scikit-learn, TensorFlow, PyTorch, PyCharm, KerasData Visualization: Tableau, Power BI, Advanced Excel Statistics and MachineLearning:NLP, Clustering Techniques, Neural Networks, Regression, Classification Models, Statistical Analysis, NLTK, Time Series Analysis, Fraud detection, Sentiment Analysis, Text Analytics, Learning Deep, Predictive Analysis, Image Recognition Databases: MySQL, PostgreSQL, SQL Server, MongoDBCloud Technologies AWS, Microsoft AzureOther Technical Skills: Microsoft SQL Server, SSIS, SSRS, SSAS, ETL Tools, Docker, Kubernetes, Informatica, Talend,Amazon Redshift, Snowflake, Apache Airflow, Data Quality and Governance, Machine Learning Algorithms, Financial Modeling, Big Data,Advance Analytics, Data Mining, Data Visualization, Data Warehousing, Data Transformation Version Control Tools: Git, GitHub, BitbucketOperating Systems: Windows, Linux, Mac IOSEDUCATIONMasters in data science, University of Maryland, Baltimore, MD, USA Bachelors in Electronics and telecommunications, Chhattisgarh Swami Vivekananda Technical University, India CERTIFICATION NVIDIADLICertificateGettingStartedwithDeepLearning Introduction to AI in the DataCenterPROFFESSIONAL EXPERIENCE Implement ML clustering for Assortment Optimization, managing multiple projects. Applied SAS macros/scripts for data manipulation, aggregation, and indexing. Build and deployed NLP projects with supervised and unsupervised learning. Conducted Nave Bayes, Cluster Analysis, and Text Mining during modeling. Develop and implement predictive models such as Logistic Regression, Support Vector Machine, Random Forest, Gradient Boosting, and KNN in Python and compare the performance. Utilize Python (Pandas, Scikit-Learn) for data preprocessing, handling imputation, outlier detection, label encoding, scaling, resampling, and feature engineering. Create visualizations (Bars, Lines, Pies, Scatter plots, Histograms) with SAS, applying various filters. Collaborated in cross-functional teams for continuous support. Work with tools like D-Beaver, SQL, Teradata, Hadoop 3.0, Trino, Druid, ML-Flow, Linux, and Git. Developed end- to-end data science pipelines in production. Develop dashboards for Product Review projects covering Topic model, Sentiment Analysis, Safety, Live Chat, and social media platform analysis. Developed waterfall graphs in SEEQ for Feature extraction and Exploratory analysis to carry out any hidden trends or seasonality residing inside the material flow data and used Grafana to create interactive and meaningful dashboards. Designed and used of analysis such as regression analysis, decision trees, time series analysis, principal component analysis, computed various machine learning algorithms like Random Forest classifier, XGB classifier etc. to find the key variable responsible for bubble break. Extracted statistics for key variables to find optimal range which would reduce bubble break frequency to drive meaningful improvements to production control and customer experience. Introduced a predictive model to a production environment. Optimized the bubble life cycle and increased company productivity and efficiency by 10 %. Developed intricate algorithms based on deep-dive statistical analysis and predictive data modeling that were used to deepen relationships and personalize interactions with customers. Wrangled/Cleaned and Merged Data with Excel, AWS S3 bucket, SQL, and Tableau. Worked with Statistics and Machine learning algorithms like Regressions (linear, logistic), ANOVA, Hypothesis Testing, A/B Testing, Classification, SVMs, Decision Trees, Random Forests, Naive Bayes, KNN, CNN, LSTM, RNN and K-means. Implemented Data preprocessing, Natural Language Processing (NLP), and Outlier Detection techniques. Used Predictive Analysis and Machine Learning techniques to forecast the company's sales and revenue for the upcoming month/quarter with 90% accuracy. Designed and created database architecture in MySQL individually for employers and managers. Developed a Pyspark model for efficient data storage in AWS Storage Gateway, optimizing data retrieval and enabling seamless querying for analytical purposes. Experienced in Information retrieval, evaluating Bigdata pertaining to EMR (Electronic Medical Records) to estimate a person's risk score. early completion of project got us 2 new projects with client. Assisted in the design, development and implementation of an enterprise reporting architecture and provide SQL Server expertise to other areas of the organization. Experienced in the end-to-end data science process, including data ingestion, exploratory data analysis (EDA), model development, and automated storing and deployment processes. Conducted web scraping using Beautiful Soup, Urllib, and Selenium for a Data Lake project, populating AWS S3 storage with results. Utilized advanced machine learning models to enhance real-time data analysis, improving predictive analytics accuracy and efficiency significantly. Applied statistical techniques and data visualization for actionable insights, contributing to data-driven decision- making processes from real-time data. Collaborated cross-functional team in designing and deploying a scalable data infrastructure, ensuring robustness and adaptability.Data Scientist HCL Technologies, India Mar 2018 Dec 2019 Data Scientist KPMG, NC Mar 2021 - Feb 2022Data Scientist Walmart, NC Mar 2022-PresentData Scientist Softage Group, India Oct 2015 - Feb 2018 |
