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Senior Data Scientist Resume

Phoenix, AZ

PROFESSIONAL SUMMARY:

  • Have unique combination of data science and technology strategy and expertise with an experience of over 25 years as a research scientist, data scientist, product/engineering manager, people manager and architect.
  • Extensively managed and lead R&D projects that involve business insights and analytics through predictive modeling, big data systems and Web based software development.
  • Expertise and experience in specific domains - B2B bid response pricing, Confidential pricing and revenue optimization, customer conversion and retention modeling, fraud and other anomaly detection, competition - tactics and strategy, advertisement budget optimization, and supply chain - demand forecasting, capacity planning and inventory optimization.

FUNCTIONAL AND ALGORITHMS EXPERTISE:

  • Statistical Machine Learning, Hypothesis Testing, Classification and Regression. Feature Engineering, NLP, Pattern recognition (used in Forecasting) and Clustering - Market Segmentation, Anomaly Detection for Intrusion Detection and IOT, User/Item Based Recommenders: Collaborative Filtering.
  • Time Series Analysis and Modeling, Forecasting, Moving Averages, Exponential Smoothing, and ARIMA
  • Optimization - Cyclic and Safety Inventory Optimization, Bidding/Pricing and Revenue Optimization, Advertisement Budget Optimization

TECHNICAL SKILLS:

Software Tools Architecture and Design ML: Python Pandas, NumPy, Scipy, Scikit-learn, NLTK, Open NLP, R, Matlab, Tkinter, Jupyter Notebook

ML/DL: Spark ML/MLLib, Mahout, Weka, DL4j, Mallet, MOA, ELKI

Big Data: Apache Spark MLLib, Spark ML with Hadoop/YARN; AWS S3, EC2

Languages: Java, Python, Scala, JavaScript, D3.js, XML, JSON and SQL

PROFESSIONAL EXPERIENCE:

Confidential, Phoenix, AZ

Senior Data Scientist

Responsibilities:

  • Prognostics and Diagnostics of Aircraft Mission Critical Systems
  • Detect the failure modes of aircraft LRUs: engine, landing gear, and pneumatic systems
  • Data mining from repositories, conditioning data, developing models, creating visualizations, preparing technical presentations and documenting the development.
  • Multivariate data models: Hotelling T Square and Q Statistics (fault diagnostics), and RNN: LSTM (fault prognostics)and PCA to find feature importance and reduce dimensions.
  • Python, Keras and Tensorflow, Pandas, Numpy, Scikit-learn, Jupyter, etc.

Confidential, Cupertino, CA

Sr. Director and Chief Data Scientist

Responsibilities:

  • As Director, built the business insights (data science) and relevant technology team to develop predictive models using structured, semi-structured and unstructured data. Mentored data analysts to come up to speed with the projects. Clarified project objectives, delegated responsibilities, and delivered results to executive management.
  • As Data Scientist, developed predictive models for classification, regression and clustering problems. Developed standards and created patents and copy rights.
  • As Product Manager interacted with clients, captured and documented business requirements; advocated clients on potential concepts, system functionality and use cases. Interfaced with development teams to ensure the schedules and accuracy in the delivery of use cases.
  • Develop classification and clustering models for customer conversion (from free users to paid users), and retention of existing customers.
  • Develop analytics to identify and study the effect of features influencing conversion and retention.
  • Responsible for data extraction, preprocessing, model evaluation, and visualizations.
  • Developed a logistic regression model to find probabilities of customer conversion
  • Architect and design the application to deploy in a multi-node cluster environment.

Tools: Scala or Java, Python, Scikit learn, MLLib, Spark ML, Hadoop, Spark RDDs, Spark SQL, and R/RStudio/SparkR Visualizations

Product Dev.

Confidential

Responsibilities:

  • Develop a clustering model based fraud detection system.
  • Responsible for data extraction, visualization, preprocessing, model evaluation, and post-processing.
  • Used K Means based model. Developed optimal number of clusters.
  • Generated the mean entropy of clusters and F1 score to evaluate model relevance.
  • Architected and designed the application to deploy in a multi-node cluster environment.

Tools: Scala, Java, MLLib, Spark ML, Hadoop, Spark RDDs, Spark SQL, and R/RStudio/SparkR Visualizations

Product Dev.

Confidential

Responsibilities:

  • Pricing models/algorithms development - Price analytics, market sensitivity analysis, market segmentation, tactical promotion planning.
  • Designed APIs for clustering/segmentation: Kmeans for customer segmentation.
  • Developed best response functions to deal with pricing from competitors based on game theory.
  • Developed optimization models to generate margin maximization.
  • Created a proprietary multi-recursive market segmentation and optimization algorithm.

Environment: Python: Scikit-Learn, Hadoop HDFS, Spark, MLLib, Java API, MySQL, SQL and Eclipse

Product Dev.

Confidential

Responsibilities:

  • Responsible for price segmentation/clustering and models development and code delivery.
  • Conducted comparison studies on Classification algorithms to decide the best response (LR) model.
  • Designed APIs for bidding LR algorithms and Machine Learning based clustering/segmentation: Kmeans.
  • Preprocessed data and compressed training sets through dimensionality reduction through LDA.
  • Tuned and tested algorithms for performance - accuracy and speed.

Environment: Python (x, y): Scikit-Learn, SQL, Java, J2EE, HDFS, MapReduce, MySQL DB

Application Architect

Confidential, Seattle, WA

Responsibilities:

  • Reviewed functional requirements; proposed system requirements.
  • Architected and designed a data-driven remote multiplexer XMA8/16 setup software.
  • Proposed architectural standards: highly extensible pipelines-elements grid model.
  • Wrote architecture document.
  • Architected the systems to be avionics MDL and iNet compliant, and vendor agnostic.
  • Identified and designed the client, client proxy, remote server and repository.
  • Architected the key subsystem interfaces: multiplexer and MDL models, data transfer processes, etc.
  • Acted as one of the key persons to communicate project development with management;
  • Used Agile& Scrum.

Technologies Utilized: Java/J2EE, Spring DI, MVC, JPA, RESTful, JAXB, Angular JS, Jackson, XML.

Confidential, Plano, TX

Senior Data Scientist

Responsibilities:

  • Created models - used extrapolation based smoothing, and pattern recognition based algorithms to minimize statistical errors - MAPE, MAD, and MSE.
  • Models operated well with level, trend and seasonal data and also for data with variance in trend.
  • Developed causal forecasting models using multi-variate regression - pricing, ad budget, team size.
  • Developed API interfaces to work with inventory optimization models and related data.
  • Supported the team with analytical modeling and algorithms through the life cycle of product.

Environment: Java/J2EE, Numerical Recipes, Struts, SQL, Oracle DB, Tomcat 6.0, Eclipse IDE

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