My CV

Bolanle Egbedokun

Nigerian

Data Scientist

SUMMARY

To employ the power of cognitive technology to develop solutions for Global
Companies. A full-time Data Scientist/Machine Learning Engineer that utilizes
machine learning and Business Intelligence skills for advance cutting-edge
technologies, developing robust applications.

ADDRESS

1, Ajike Faleye street,
Orelope, Egbeda, Lagos
state.

WORK EXPERIENCE

PagaTech, Lagos NG — Data & Strategy Associate
JUNE 2018 - PRESENT
  • Demonstrating expertise in handling unique data analysis requests using hot technologies.
  • Offer assistance/guidance related to data analysis to the business and explains how it impact the business
  • Query data, understand the results, and make the data easy to understand.
  • Understand all business data, sales, claims, payments, and pulling with SQL statements
  • Recommend process improvements and improvements to data visualization
  • Build both automated and ad hoc reports in support of various stakeholders
  • Design, build and maintain dashboards to determine KPIs to aid reporting and analysis.
  • Mentor users and lower-level BI Analysts
  • Agile Project Management
  • Use data to create models that depicts trends in the customer base and the consumer population as a whole.
  • Work with management team to create a prioritized list of needs for each business segment.
Dbrown Consulting, Lagos NG — Business Intelligence
Analyst
SEPTEMBER 2016 - APRIL 2018
  • Monitor analytics and metrics results
  • Implement new data analysis methodologies
  • Review customer files to ensure the integrity of data collection and utilization
  • Enhancing data collection procedures to include information that is relevant for building analytic systems
  • Creating automated anomaly detection systems and constant tracking of its performance
  • Processing, cleansing, and verifying the integrity of data used for analysis
  • Doing the ad-hoc analysis and presenting results in a clear manner
  • Develop policies and procedures for the collection and analysis of data
  • Create or discover new data procurement and processing programs
  • Cooperate with our IT department to deploy software and hardware upgrades that make it possible for us to leverage big data use cases
  • Build and maintain dashboards for clients and the firm.
  • Build detailed and automated reporting tools using Microsoft business intelligence technologies
  • Develop, Calculate & monitor client KPI’s.
A.C Nielsen Nigeria, Lagos NG **—** Quality Control
Analyst
OCTOBER 2012 - JULY 2016
  • Determining best results by using massive amount of data
  • Quantifying results beyond pass or fail
  • using machine learning to optimize test runs
  • Identifying methods and processes on improving operations efficiencies.

SKILLS

  • Microsoft Azure Machine learning/Cortana Intelligence Suite
  • Azure Portal (HDInsight - Hadoop (Hive), HBase, Spark, and R Server (with R Studio)
  • Bigdata, Machine Learning, Deep Learning, Agile (SaaS)
  • Experience working with cloud computing platforms like Microsoft Azure Portal & AWS
  • R & R packages, Python, C/C++, Machine Learning Algorithms & R/python scripts & notebooks.
  • Data Visualisation tools

LANGUAGES

English

PROGRAMMING LANGUAGES

  • Python, R, Mathlab,
  • Octave, Hadoop, Spark,
  • SQL, C++, Html, CSS & Flask

INTERESTS

  • Technology
  • Reseach
  • Football

EDUCATION

Open Source Society University | 2020, Online — BSC

CERTIFICATION

  • Microsoft Professional Degree in data science - 2016
  • Microsoft Partner University - Advance Analytics For Data Analytics (Machine Learning Competency)
  • Microsoft Partner University - Bigdata For Data Analytics(Competency)
  • TU Delft University of Technology eDX DELFTX - Professional Certificate Program in Data Science.

PROFESSIONAL DEVELOPMENT

  • edX, Inc. (MOOC platform)
  • Address: 141 Portland St, Cambridge, MA 02139, United States

Used edX.org, a massive open online course (MOOC) platform, to take courses

offered by accredited Universities and training programs, including Harvard and

Microsoft, to acquire skills in: C, Python, Mathlab, Octave, Excel and More.

Analysing and Visualizing Data with Excel – Microsoft (2016) edX

Learned to create models in order to explore, analyse and visualize data.

Data Analysis & Statistics: Take it to the MAX() – TU Delft University of

Technology, Nederland (2016). Learned to enhance unique data analysis skills

using spreadsheets and data visualization.

Data Analysis: Visualization and Dashboard Design – TU Delft University of

Technology, Nederland (2015/2016). Learned how to turn raw data into visual

insights using Excel to help support business decisions.

Data Analysis: Building Your Own Business Dashboard – TU Delft University of

Technology, Nederland (2016) edX. Learned to dive in headfirst and carry out an

independent data analysis. Built and designed dashboards Based on raw data to

better inform business decisions.

Microsoft Data Science Professional Project - Microsoft (2016) edX.

A Capstone project for the Microsoft Professional Degree in data science.

Machine Learning ColumbiaX - CSMM.102x - Columbia University (2016/2017)

Major perspectives covered include: probabilistic versus non-probabilistic

modelling, supervised versus unsupervised learning

Introduction to Computer Science and Programming Using Python – MITx edX.

A Notion of computation, The Python programming language, Data structures

and Algorithms and more.

Managing Projects with Microsoft Project - Microsoft (2016/2017)

Using the Project App within Microsoft Office 365, Planning and Designing your

project within Microsoft Project, Best practices in using Microsoft Project

Programming with R for Data Science – Microsoft (2016/2017) edX

Explore R language fundamentals, including basic syntax, variables, and types,

How to create functions and use control flow. Details on reading and writing

data in R, Work with data in R, Create and customize visualizations using

ggplot2, Perform predictive analytics using R.

Applied Machine Learning – Microsoft (2016/2017) edX

Explore analysis of time series and forecasting, look at spatial data analysis,

Learned about text analytics, Review analysis of images.

Principles of Machine Learning - Microsoft (2016/2017) edX learned

how to build predictive analytics solutions with Azure Machine Learning,

perspectives covered includes Classification and Regression models, Improving

Machine Learning models, Tree and Ensemble methods, Neural networks and

SVMs, Clustering and Recommenders.

Agile Development Using Ruby on Rails - The Basics - BerkeleyX -

CS169.1x(2017) Learned Ruby programming language basics, the Ruby on Rails

Model-View-Controller (MVC) development framework and software

engineering fundamentals.

LAFF: Linear Algebra - Foundations to Frontiers - UTAustinX - UT.5.05x(The

University of Texas)017 studied Vector and Matrix Operations, Linear

Transformations, Solving Systems of Equations, Vector Spaces, Linear Least-

Squares, and Eigenvalues and Eigenvectors. In addition, got a glimpse of cutting

edge research on the development of linear algebra libraries, which are used

throughout computational science.

Machine Learning Stanford University – Stanford University Machine Learning

Course taught by Professor Andrew NG. Learned Linear Regression, Linear

Algebra, Logistic Regression, Regularization, Neural Networks, Machine Learning

System Design, Support Vector Machines, Unsupervised Learning(Dimensionality

Reduction, Anomaly Detection, Recommender Systems, Large Scale Machine

Learning).

PROJECTS & BLOG

Data Science & Machine learning projects

Hands_On_DataScience_Projects
Machine_learning_Projects_with_Python
My Blog

HOBBIES

Coding/Programming

Research

REFERENCE

Name: Oluwatoyin Animashaun
Address: 20, owokoniran str, council b/stop,
Lagos State.
Tel: +
Email: oluwatoyinanimashaun@gmail.com

Name: Ogbonna Wosu
Address: 6, Obokun close, Ikeja, Lagos state.
Tel: +
Email: owosu@yahoo.com