SUMMARY

• Over 7+ years experience working as a Data Scientist with math/statistics/probability/data modeling background, and with analytical software/languages (e.g. SAS)
• Expert in traditional (Waterfall Approach), Rational Unified Process and Agile (Scrum) project methodologies

TECHNICAL SKILLS

• Python
• SAS
• R
• Tableau
• KNIME
• Spark
• Toad
• Machine Learning
• NLP
• Microsoft Office (Access
• Excel
• Outlook
• PowerPoint)
• PL/SQL
• HP Quality Center
• SharePoint
• Finacle
• MS Visio.

PROFESSIONAL EXPERIENCE

Data Scientist

Confidential, Chicago, IL

Responsibilities:

• Determine data structures and their relations in supporting business objectives and provides useful data in reports.
• Experience in managing and reviewingHadooplog files
• Performed data analysis utilizing SAS Enterprise Guide and Excel.
• Responsible for implementing the covariance regression model and related statistical tests, correlation analysis, back testing, outcome/sensitivity analysis in R.
• Experience with data mining and analytics methods (e.g., clustering, sequences, networks, time series, deep learning, statistical analytics, etc.).
• Applied Machine Learning experience (regression analysis, time series, probabilistic models, supervised classification and unsupervised learning).
• Strong mathematical background (linear algebra, calculus, probability and statistics).
• Collaborate with other analysts and key stakeholders to identify underlying trends, both internal and external, impacting current and future enrollment and financial considerations, and in corporate trends into forecast models
• Work with diverse data sets, identify and develop valuable new sources of data and collaborate with product teams to ensure successful integration

Data Scientist / Business Analyst / Team Lead

Confidential, Greenbelt MD

Responsibilities:

• Interprets and documents Agency and component data information needs, including business rules.
• Built and managed talented teams of business analysts, programmers, developers and other specialists.
• Analyzed data from the monthly statistics to identify profitable marketing channels to maximize ROI.
• Created analysis model to optimize resource allocation and predict client outcomes.
• Assist in development of process documentation; monitoring, tracking and reporting status of organization initiatives, and developing performance metrics for initiatives.
• Knowledge of data mining and machine learning algorithms, theories, principals and practices.
• Experience with data manipulation, analytic tools, and data visualization
• Obtain functional requirements from subject matter experts during group workshops or follow - up interviews.
• Analyzing and modeling structured data using advanced statistical methods and implementing algorithms and software needed to perform analyses
• Determine data structures and their relations in supporting business objectives and provides useful data in reports.
• Document and describe logical data models, semantic data models and physical data models.
• Identify important and interesting questions about large datasets, then translate those questions into concrete analytical tasks.
• Analyzed financial data for prospective purchase, asset allocation, fee generation or other cash flow, using typically industry/company standard analytical tools or measures.
• Uses and learns a wide variety of tools and languages to achieve results (e.g., R, SAS, Python, SQL)

Data Scientist

Confidential, Bowie MD

Responsibilities:

• Assisted the team to provide recommendations by drawing out key insights mathematically from disparate data sources.
• Outlined plan of execution to leverage predictive models and other machine learning algorithms as part of companytechnology strategy
• Perform machine learning, natural language, and statistical analysis methods, such as clustering and classification, collaborative filtering, association rules, sentiment analysis, topic modeling, time-series analysis, multivariate regression analysis, statistical inference, and validation methods
• Perform complex modeling, simulation and analysis of data and processes
• Conceptualize analysis processes that will use mechanisms such as algorithms, statistical sampling, regression analysis
• Conduct and interpret multivariate analyses examples, including regressions with various distributions and duration models.
• Collaborate with other analysts and key stakeholders to identify underlying trends, both internal and external, impacting current and future enrollment and financial considerations, and in corporate trends into forecast models
• Proficiency in analysis (e.g. R, SAS) packages, programming languages (e.g. Python) as well as the ability to implement, maintain, and troubleshoot big data infrastructure, such as distributed processing paradigms, stream processing and databases such as SQL

Data Scientist

Confidential

Responsibilities:

• Collaborated with cross-functional teams such as data onboarding, functional requirements group and development team to help map exchange data in to a normalized model.
• Update, maintain and validate large financial data sets for derivatives using SQL.
• Provided root cause analysis and preventative measures for any data quality issues that occurred in day to day operations to clients.
• Use advanced data mining, statistical analysis, machine-learning and visualization techniques to create solutions to challenging real-world problems
• Work with diverse data sets, identify and develop valuable new sources of data and collaborate with product teams to ensure successful integration
• Fraud detection & automated ranking content quality
• Created customized reports and processes in SAS and Tableau Desktop