Data Project

Abiola Ijaola *********@*****.*** 240-***-****

Summary

Over 11+ 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

Skills

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

Professional Experience

Data Scientist

Baltimore Accenture / Pace Computer Solutions

November 2016 - Present

Project Summary Fraud detection on MySSA (Social Security Administration) project and I have an active public trust clearance.

Determine data structures and their relations in supporting business objectives and provides useful data in reports.

Developed statistical models for analysis and planning purposes.

Experience in managing and reviewing Hadoop log files

Performed data analysis utilizing SAS Enterprise Guide and Excel.

Strong background in machine learning and deep learning networks

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 incorporate trends into forecast models

Work independently to develop models that address specific business problems related to enrollment management, retention, marketing and class scheduling

Perform complex modeling, simulation and analysis of data and processes

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

Fairfax Virginia PBGC / SalientCRGT

September 2014 – November 2016

Project Summary Data Scientist on PBGC (Pension Benefit Guaranty Corporation) project.

Identifying, gathering, and analyzing complex, multi-dimensional datasets utilizing a variety of tools.

Built and managed talented teams of business analysts, programmers, developers and other specialists.

Interface directly with client stakeholders providing trusted advice and recommendations on programmatic and technical items for current project with Federal Protective Services.

Performed data visualization and developed presentation material utilizing Tableau.

Assisted the project managers and directors to develop, plan and maintain a detailed project schedule which includes administrative tasks that were involved in the projects.

Working with clients in defining the key business problems to be solved while developing, maintaining and leveraging key client relationships

Experienced in using agile approaches, including Extreme Programming, Test-Driven Development and Agile Scrum.

Maintaining knowledge and understanding of current and emerging trends within the analytics industry

Manage timelines and facilitate planning meetings with clients and internal staff meetings.

Participate in product redesigns and enhancements to know how the changes will be tracked and suggest product direction based on data patterns.

Strong foundation in statistics -Mining and organizing datasets of both structured and unstructured data: preferably large datasets

Knowledge of algorithms, data structures and performance optimization

Experience with applied statistics and/or applied mathematics

Document areas of progress and track in spreadsheet on project, including managing the completion of the deliverables across the project lifecycle.

Facilitate the data collection sessions. Analyze and document data processes, scenarios, and information flow.

Determine data structures and their relations in supporting business objectives and provides useful data in reports.

Develop / improve stakeholder communication and coordination across internal and external organizations, such as other federal agencies, States, and industry

Promoted enterprise-wide business intelligence by enabling report access in SAS BI Portal and on Tableau Server

Utilizes tools such as Python, Tableau, SAS, etc. to perform complex data analysis

Data Scientist / Business Analyst / Team Lead Jrock Technologies

Greenbelt MD

January 2013 – September 2014

Project Summary Online Loan Application System to automate loan approval processes.

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

Facilitate the data collection sessions. Analyze and document data processes, scenarios, and information flow.

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 Vogo Technologies

Bowie MD

September 2010 to December 2012

Define the requirements and make recommendations on tools and capabilities to further data analytic capabilities.

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 company technology 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

Visualizations and optimization techniques

Summarize data through various tabular and visual modes

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 incorporate trends into forecast models

Work independently to develop models that address specific business problems related to enrollment management, retention, marketing and class scheduling

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 Ecobank

March 2007 to September 2010

Strong communication skills.

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

Identify and analyze anomalous data (including metadata)

Analyze data using appropriate tool set

Evaluate research for practical application

Analyze data using mathematical/statistical methods

Apply mathematical and computation methods and lines of reasoning

Fraud detection & automated ranking content quality

Created customized reports and processes in SAS and Tableau Desktop

Education

B.Sc Mathematics / Statistics University Of Lagos, Nigeria (2006)

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