Ritin Chandra Email and Phone Number
As a Data Scientist with over 10 years of experience, I have demonstrated expertise in machine learning, artificial intelligence, and data analysis. My proficiency in Python, R, SQL, and various data science tools, combined with my extensive experience in advanced analytics and predictive modeling, enables me to deliver actionable insights that drive business growth.I have a strong background in utilizing Python-integrated IDEs like Anaconda and PyCharm, optimizing development workflows and enhancing productivity. My experience extends to developing Power BI datasets and reports, including managing import and direct query modes, and scheduling refreshes to ensure up-to-date insights.My skills include developing and implementing predictive models using a variety of techniques such as decision trees, random forest, naive Bayes, logistic regression, and neural networks. I am well-versed in natural language processing (NLP) and time series forecasting using RNNs, LSTMs, ARIMA, and SARIMA, enabling advanced analysis and forecasting capabilities.I have hands-on experience with big data technologies and platforms, including Hadoop, Spark, and Google Cloud Platform (GCP). This includes data ingestion, storage, querying, and processing, as well as developing Spark applications for real-time data analysis and transformation. My proficiency extends to creating machine learning back-end pipelines and implementing MLOps practices for streamlined model deployment and monitoring.I am skilled in utilizing report development tools such as Report Wizard, Report Builder, and Report Manager in SSRS and Power BI, and have experience with version control systems like Subversion and Git. My expertise also includes working with various open-source business intelligence tools like Knime and Metabase, and developing complex ETL processes and machine learning models for fraud detection and advanced analytics.With a proven track record of collaborating with business stakeholders and subject matter experts, I excel in gathering requirements, aligning data solutions with business objectives, and delivering impactful results. My background in statistical modeling and machine learning algorithms, combined with a strong focus on continuous improvement and efficiency, positions me well to contribute valuable insights and drive data-driven decision-making.If you are seeking a highly skilled and experienced Data Scientist with a robust background in machine learning, big data, and advanced analytics, I would welcome the opportunity to leverage my expertise to benefit your team.
Fannie Mae
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Senior Data ScientistFannie Mae Mar 2022 - PresentWashington, United States• Implemented an AI-powered chatbot, reducing response times by 30%.• Developed and maintained advanced ML platforms within an end-to-end MLOps framework for seamless model integration.• Optimized business operations with advanced analytics and ML algorithms, increasing profitability by 15%.• Collaborated with teams to deploy predictive models, improving customer engagement by 20%.• Created end-to-end data pipelines with Azure Data Factory for seamless data orchestration.• Provided predictive and prescriptive analytics to drive profits and efficiencies.• Built ML algorithms to enhance productivity, loyalty programs, and marketing effectiveness.• Identified new data sources for ML and AI solutions.• Developed complex ETL jobs using Azure Databricks and Azure SQL Database.• Implemented tools and best practices for deployment success, including a new SDLC process.• Built and trained multi-layered Neural Networks using TensorFlow, Keras, KNIME, and Azure ML Studio.• Conducted statistical analyses like linear regression, ANOVA, and classification models.• Deployed ML models into production with containerization, API development, and system integration.• Explored and implemented AI techniques, including open-source Gen AI LLMs (Llama, Dolly).• Performed sentiment analysis using NLP libraries (NLTK, SpaCy, Gensim, TextBlob).• Predicted customer churn with an ANN classifier in an ML-LTV pipeline.• Created analytics dashboards with Power BI depicting critical KPIs and enabling end-user filtering.• Built data pipelines with Python and Kafka for data ingestion into Azure Data Factory.• Designed dashboards and reports with Tableau and Power BI, providing insights to stakeholders.• Developed table visuals using Power BI Report Builder.• Utilized NLP applications for topic modeling and sentiment analysis to identify data trends and patterns.
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Senior Data ScientistCentene Corporation Jun 2021 - Feb 2022St Louis, Missouri, United States• Applied advanced ML techniques (Gradient Boosting, Random Forest, GLM) for high-accuracy predictions and analytical insights.• Performed end-to-end integration and validation testing of patient care models and systems (PRM, Jacada, IQVIA, Prometrics, Data Lake, Pharmacy solutions) to ensure data integrity.• Developed and implemented Marketing Mix Models to measure marketing channels' impact on sales performance.• Utilized statistical techniques (synthetic control) and software (R, Python) to analyze historical marketing data.• Worked with data scientists, analysts, data engineers, and QA engineers to generate and deploy analytical solutions.• Developed scalable ML algorithms for predictive modeling using PyTorch, Spark, SparkML, and Scikit-learn.• Analyzed insurance claims data to identify fraudulent patterns.• Collaborated with Marketing, Product, Sales, Risk Management, Claims Processing, and IT teams to integrate solutions.• Built data pipelines to unify data from disparate sources.• Developed a customer tiering program using Python, R, AWS, and Docker.• Created custom data visualization solutions using Tableau, R-Shiny, and R packages.• Established CI/CD pipelines for automated ML model training, testing, and deployment.• Influenced decision-making across HPWS with data-driven insights and MLOps best practices.• Supported marketing campaigns with forecast models and personalized rebate offers using R and AWS.• Developed R and Shiny applications for business forecasting.• Collaborated with IT on analytics tools testing.• Used agile methodology for building data science products.• Designed ETL processes and documented source-to-target mappings, transformations, and aggregations.• Written SQL queries, procedures, and merge statements for data retrieval and destination table updates.• Worked with Amazon SageMaker for preparing, building, training, and deploying ML models.• Coordinated and controlled BI data flow between sources and end-users. -
Senior Data ScientistWells Fargo Sep 2019 - May 2021Santa Clara, California, United States• Implemented OLAP multidimensional cube functionality with Azure SQL Data Warehouse.• Performed ANOVA, linear regression, and logistic regression using Python and Advanced MS Excel.• Leveraged NLP libraries (NLTK, TextBlob, SpaCy, Gensim) for improved textual information analysis.• Utilized Apache Spark with Python for Big Data Analytics and ML applications, executed ML use cases with Spark ML and Mllib, and aggregated log data using Storm and HDFS.• Conducted fraud analysis in healthcare data, ensuring regulatory compliance.• Built DNNs with Keras, Azure ML Studio, TensorFlow, and SVMs for invoice claim predictions.• Ingested data into Azure services (Data Lake, Storage, SQL, DW) and processed it in Azure Databricks.• Developed predictive models for patient outcomes and fraud detection.• Performed data integrity checks, cleansing, exploratory analysis, and feature engineering with Python libraries (Pandas, Matplotlib).• Programmed in Spark and Python for data pipelines and insights.• Used Spark Streaming for continuous data analysis with PySpark.• Identified outliers in datasets using R Studio for fraud detection.• Resolved complex issues in Azure Databricks and HDInsight.• Built predictive models (SVM, Decision Tree, Naive Bayes, Neural Network, ensemble methods) with scikit-learn.• Designed dashboards and visualizations with Tableau , and provided complex reports.• Built predictive models (Linear Regression, AR, MA, ARMA, ARIMA) for sales predictions with scikit-learn and StatsModels.• Used Elastic Search for data retrieval.• Managed data quality and integrity in Data Warehousing, Databases, and ETL. -
Data ScientistAlbertsons May 2017 - Aug 2019Pleasanton, California, United States• Spearhead data analysis initiatives to extract insights from large datasets, driving informed decision-making and strategic planning• Conduct exploratory data analysis (EDA) to uncover trends, patterns, and anomalies, guiding business strategy and resource allocation.• Implement data preprocessing techniques including data cleaning, feature engineering, and normalization to improve model• I worked on different machine learning algorithms for ticket classification system by training and fine-tuning models using labeled ticket• Evaluate the developed model aiming to have which is both accurate and reliable, using standard evaluation metrics based on purpose• Communicate findings and recommendations to stakeholders through clear and concise data visualizations, reports, and presentations.• I worked extensively on SQL queries and jobs that were used to analyze and process payroll data to generate reports.• Worked on specific modules of applications responsible for generating reports using SSIS and SSRS.• I handled sensitive data while ensuring its integrity remained uncompromised, without any issues.• Engaged in cross-collaboration with various teams to ensure smooth data flow, and in case of any issues, collaborated with them to efficiently resolve and run cycles.• Mentor junior team members and provide technical guidance on best practices in implementing effective solutions.• Stay abreast of the latest developments in data science, machine learning, and AI technologies, integrating new tools and methodologies -
Data AnalystFrux Software Solutions Pvt Ltd May 2013 - Dec 2016India• Spearhead data analysis initiatives to extract insights from large datasets, driving informed decision-making and strategic planning• Conduct exploratory data analysis (EDA) to uncover trends, patterns, and anomalies, guiding business strategy and resource allocation.• Implement data preprocessing techniques including data cleaning, feature engineering, and normalization to improve model• I worked on different machine learning algorithms for ticket classification system by training and fine-tuning models using labeled ticket• Evaluate the developed model aiming to have which is both accurate and reliable, using standard evaluation metrics based on purpose• Communicate findings and recommendations to stakeholders through clear and concise data visualizations, reports, and presentations.• I worked extensively on SQL queries and jobs that were used to analyze and process payroll data to generate reports.• Worked on specific modules of applications responsible for generating reports using SSIS and SSRS.• I handled sensitive data while ensuring its integrity remained uncompromised, without any issues.• Engaged in cross-collaboration with various teams to ensure smooth data flow, and in case of any issues, collaborated with them to efficiently resolve and run cycles.• Mentor junior team members and provide technical guidance on best practices in implementing effective solutions.• Stay abreast of the latest developments in data science, machine learning, and AI technologies, integrating new tools and methodologies
Frequently Asked Questions about Ritin Chandra
What company does Ritin Chandra work for?
Ritin Chandra works for Fannie Mae
What is Ritin Chandra's role at the current company?
Ritin Chandra's current role is Data Scientist | Machine Learning| Predictive Modeling| Big Data| Azure| Python| SQL| Power BI| Tableau| NLP| Spark| Data Warehousing| Feature Engineering| Data Visualization..
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