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Lessons offered by Oladotun
  • Individual
The lessons will be held
Taught subjects
  • Computer programming
  • C++
  • Computer languages
  • Python
  • Java
  • Artificial intelligence
Levels
  • Elementary School
  • Middle School
  • Sophomore
  • Junior
  • Senior
  • Advanced Technical Certificate
  • College
  • Adult Education
  • MBA
  • Beginner
  • Intermediate
  • Advanced
  • Proficient
  • For children

Data Scientist with over 5 years of experience in Massachusetts, BSC and Masters in Computer science.

Methodology

As a tutor, my teaching methodology is based on understanding student needs and perspectives. I take the approach that everyone can learn and it is just a matter of explaining the material in a way that adheres to the student's needs.

Background

Dotun Opasina is a data Scientist interested in creating meaningful impact in the world. He earned a master’s degree in Engineering Management from Johns Hopkins University and was a software engineer building data systems that served clients at Goldman Sachs. He is currently getting a masters in data science in the Massachusetts area. His professional interests lie in creating and analyzing datasets that create a positive influence on the world. He has worked on multiple data science including creating a crowdfunding predictor for Kickstarter using Neural Networks to help customers reach their goals. He currently resides in the USA and he is originally from Nigeria.

Rates

Rate for online lessons : $20/h
Lessons offered by Oladotun
Individual
The lessons will be held
at your home
Taught subjects
  • Computer programming
  • C++
  • Computer languages
  • Python
  • Java
  • Artificial intelligence
Levels
  • Elementary School
  • Middle School
  • Sophomore
  • Junior
  • Senior
  • Advanced Technical Certificate
  • College
  • Adult Education
  • MBA
  • Beginner
  • Intermediate
  • Advanced
  • Proficient
  • For children

Oladotun's resume

Summary
Data scientist with a background in financial services technology. Highly skilled in data analysis, modelling and data visualization. Proficient using Python, R, SQL, AWS and utilizing large datasets to solve business problems.

Education and Training:
Fitchburg State University Fitchburg, Massachusetts
Computer Science(MSc.); Data Science; GPA: 3.92 December 2020

Johns Hopkins University Baltimore, Maryland
Engineering Management (MSc.); GPA: 3.7 May 2016

Morgan State University Baltimore, Maryland
Electrical Engineering (BSc.); GPA:3.89 May 2013

Professional Work Experience
J.C Madigan Lancaster, Massachusetts
Data Science Intern October 2019 – Present
• Working at New England’s premier truck distributors that provides over 20 plus trucking equipment offerings to customers.
• Collaborating with Chief Technology Officer to build fleet management system from scratch to target the $20 billion trucking industry.
• Creating python programs and Tableau dashboards to mine databases containing trucking industry information used to develop a software application for salesmen.
• Developing and designing the overall system architecture for the app and performed data mining tasks.

ProfMentor Lagos, Nigeria
Technical Development Lead August 2017 – January 2019
• Built ProfMentor: an online platform to connect mentors and mentees together from scratch.
• Delegated tasks to a team of global developers to strategize and provide product improvement.
• Provided recommendations on SQL database server and PHP programming languages for ProfMentor.

Goldman Sachs New York City, New York
Summer Analyst, Analyst June 2015 – May 2017
• Created data visualization and analytics using Tableau to help investment bankers and employees in the firm.
• Created java utilities around Tableau’s server.
• Led a tutorial session for 5 VPs on performance testing that enabled them to empower their individual teams.
• Worked with a global team of technologists across Asia and Europe in accomplishing IBD’s technology goals.

Key Accomplishments
• Created software technologies that drastically reduced time required to generate reports from weeks to days (300% improvements) using Java and Javascript.
• Developed “ReportLink”: a data repository for scheduling and monitoring Business Objects using angular.

· Created a Java utility report that provided the technology team information on what Tableau workbooks /data sources were faulty which led to an improvement in their maintenance processes by 40% when evaluating data sources and workbooks.
· Created a Java utility report that periodically emailed users during Tableau refresh extract failures
· Utilized Tableau’s Desktop to create workbooks and data sources used by team and peers that reduced employee time spent by 45% in searching for Tableau information.





Data Science Projects
Predicting House Prices Using Regression Algorithms
• Project focused on creating a predictor using regression algorithms to predict house prices in Massachusetts area.
• Built a flask web application that allow users enter inputs to predict house prices.
• Results enabled users draft multiple inputs to know the prices of the houses.
Using Neural Networks To Predict Funding for Kickstarter Projects
• Project created a predictor using neural networks to predict Kickstarter projects that will get funded.
• Built a flask web application to allow users to enter their inputs to predict their Kickstarter projects.
• Results showed the most important category that users need to focus on to see an increase in their Kickstart campaign funds.
Using Logistic Regression To Interpret Internet Provider Churn Data
• Project focused on churn data to figure out what sort of customers are leaving an internet service provider using Logistic regression.
• Results showed that users purchasing Fiber optics service were most likely to churn.
• Provided recommendations to the company on ways to curb users leaving an internet service provider.
Predicting NBA Player Salaries using Linear Regression
• Utilized Python and linear regression to predict NBA players’ salaries based on performance.
• Result showed that 5 out of 20 key stats metric had the most impact on players salaries such as the player’s minutes played, age, defensive rebounds, number of personal fouls and points per game.
• The result predicted the player's salaries based on their statistics.
Honors, Awards and Associations Year Awarded
· Schwarzman Scholar recipient 2018
· Johns Hopkins / Morgan State University Fellowship 2014
· Morgan Full Academic Scholarship Award & Deans’ List ` 2012 – 2014
· Morgan State University Most Outstanding Junior Scholar 2012
· Morgan State University Honors Convocation 4.0 G.P.A Award 2010
· Alpha Lambda Delta Honor Society; Phi Eta Sigma Honor Society; Grant-Promethean Kappa Tau Honor Society; National Society of Collegiate Scholars; Tau Beta Pi Engineering Honors Society; Jumpstart Undergraduate Diversity Forum; Sponsors for Educational Opportunities; National Society of Black Engineers
Teaching and Conferences
• Introduction to Data Science on YouTube Live:
o Taught over 1000+ students on an introduction to data science where we analyzed different use cases of data in different businesses.
o Received numerous positive feedback on the class and how it encouraged students to pursue a career in data science.
Leadership Experience
Johns Hopkins University Baltimore, Maryland
Graduate Representative Organization, Co-Chair May 2015 – May 2016
· Served as the co-chair of the Graduate Representative Organization (GRO), a student body organization responsible for advocating for all 7000 graduate students needs at JHU Homewood campus
· Organized events that addressed graduate student needs such as career-building and coping with mental health challenges
Volunteer Experience
Advancing Minorities Interest in Engineering, Volunteer Peer tutor August 2010- May 2016
• Tutored high school students in Mathematics and Science related subjects.
• Taught students to build engineering and computer science projects such as solar powered houses and an iPhone app.
Skills
• Technical Skills: Linux, C++, C, Python, R, SQL, Tableau, React Native, Java, AWS
o Machine Learning Skills: Regression, Classification, Neural networks, Logistic regression, Clustering.

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