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Akinwande K - keras developerLD Talent logo

Akinwande K

The star rating is calculated by averaging the reviews provided by all clients the talent has worked with for a significant amount of time.

If such data is not available, the star rating is calculated from the fraction of work sessions approved by their past clients versus the total tracked by the talent.

If such data is not available, the star rating defaults to the interview rating of the talent at the time of the vetting process.

Other data including reviews from interviews are available on the talents’ profiles but do not influence their star rating, though they do influence their position in the search results.
Software Engineer Preferred Title
$43.75 /hr $ 28.0K /yr Hourly Rate and Yearly Salary
Overview Vetting Experiences Qualifications
Overview
Basic Summary
LD Talent History
  • Worksession Approval 64.0%
  • Average Response Time 6.1 hours
  • Average Count of Messages/Day 0.9
  • Project Completion Rate 2/4
  • Interview Acceptance Rate 4/6
  • Timezone Overlap 44h PST, 49h UTC
  • Earned Hours 3.50
Vetting Summary
  • Code Quality 60%
  • Soft Skill Attributes 60%
  • Expertise 2/3
  • Coding Challenges 60%
  • No. of Lifelong Learning Projects 2
  • No. of Coding Challenges Completed 2
  • More details
Talent's Devices
  • Desktop Mac
  • Phone iPhone
General
  • Member Since Jan 27, 2020
  • Profile Last Updated Nov 14, 2021
  • Last Activity March 24, 2022, 6:52 p.m. UTC
  • Location Nigeria
Profile Summary
Adaptable Data Scientist skilled in recording, interpreting and analysing data in a fast-paced environment. Able to play a key role in analysing problems and coming up with creative solutions as well as producing methodologies and files for effective data management. A quick learner who can absorb new ideas and can communicate clearly and effectively.
Skills
Total Experience: 4 years
  • keras (1E, 4Y)

    1 experience, across 4 years
  • Python (3E, 4Y)

    3 experiences, across 4 years
  • Deep learning (1E, 4Y)

    1 experience, across 4 years
  • Machine learning (3E, 4Y)

    3 experiences, across 4 years
  • AWS S3 (1E, 4Y)

    1 experience, across 4 years
  • Web scrapers (1E, 3Y)

    1 experience, across 3 years
  • Natural language processing (1E, 3Y)

    1 experience, across 3 years
  • Python Selenium (1E, 3Y)

    1 experience, across 3 years
  • Data Science (1E, < 1Y)

    1 experience, less than a year
  • scikit-learn (1E, < 1Y)

    1 experience, less than a year
  • Docker (1E, < 1Y)

    1 experience, less than a year
  • Power BI (1E, < 1Y)

    1 experience, less than a year
  • Tableau (1E, < 1Y)

    1 experience, less than a year
  • Microsoft Excel (1E, < 1Y)

    1 experience, less than a year
  • Data Analytics (1E, < 1Y)

    1 experience, less than a year
  • MySQL (1E, < 1Y)

    1 experience, less than a year
Weekly Availability
Timezone Overlap Per Week: 44h PST, 49h UTC
Day
Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
UTC
10 - 20
13 - 19
13 - 19
13 - 19
13 - 19
14 - 20
11 - 20
PST
03 - 13
06 - 12
06 - 12
06 - 12
06 - 12
07 - 13
04 - 13
Vetting
  • Interview Data
  • Agile Development Process
  • Productivity and Responsiveness
  • Teamwork
  • Software Engineering
  • Logical Thinking
  • Technical Strength
  • Intellectual Merit
  • English Communication
  • Documentation
  • System Design
  • Coding Challenges
    60%
  • Algorithms Score
    60%
  • General Score
    60%
  • Easy Algorithm
  • Correctness
    60%
  • Performance
    60%
  • Medium Algorithm
  • Correctness
    60%
  • Performance
    60%
  • Hard Algorithm
  • Correctness
    60%
  • Performance
    60%
  • Expertise
    2/3
  • Design Patterns and Architectures
    2/3
  • Debugging
    2/3
  • Stack Traces
    2/3
  • Testing
    2/3
  • System Administration
    2/3
  • Soft Skill Attributes
    60%
  • Entrepreneurial
    60%
  • Whole Brained
    60%
  • Divergent Thinking / Creativity
    60%
  • Design Ability
    60%
  • Empathy
    60%
  • Project Management Ability
    60%
  • Security
    60%
  • Code Quality
    60%
  • Complex Logic
    60%
  • Models
    60%
  • Controllers
    60%
  • Templates
    60%
  • APIs
    60%
  • Training/Testing Data Models
    60%
  • Code Readability
    60%
  • Ongoing Evaluation
  • Number of Lifelong Learning Project
    2
  • Number of Coding Challenge Completed
    3
  • Lifelong Learning Project 1
  • Lifelong Learning Project 1
  • Coding Challenges 1
  • Coding Challenges 2
  • Coding Challenges 3
Experience
Software Engineer
Passion Project
May 2020 - Present
Tekspace Company
Technology Industry
Project: web scraping
  • Natural language processing
  • Machine learning
  • Python Selenium
  • Web scrapers
  • Python
  • Built web scrapers from scrapsfromthelofts.com with the BeautifulSoup package.
  • I used python selenium for creating the headless browser and debugged the web scraping script.
  • Used machine learning algorithms to predict sentiment of different comedians.
  • Used Natural language processing to build a sentiment analysis model.
Software Engineer
Contract
Jul 2019 - Present
Terragon group Company
Media and Communication Industry
Project: Building click through rate models
  • keras
  • Machine learning
  • Deep learning
  • AWS S3
  • Python
  • Carried out the extract, load and transform process on the data from AWS S3 with python scripts.
  • Deployed machine learning models into production as a RESTful web service.
  • Conducted cluster analysis to generate segmented profiles for customers using deep learning
  • Developed a wide and deep neural network using the Keras API to predict whether a mobile ad will be clicked or not.
Github Links
  • https://github.com/Sensei-akin/slik_python_package/
Software Engineer
Contract
Jun 2020 - Sep 2020
Ensemble lab Company
Finance Industry
Project: Building Credit risk models
  • Machine learning
  • Data Science
  • Docker
  • scikit-learn
  • Python
  • I developed a loan default model using scikit-learn API to predict if a person will default on a loan.
  • Dockerized my model in order for the API to be consumed in production.
  • Used my data science and analytical skills to effectively carry out my job.
  • Carried out the extract, load and transform process on the data from AWS S3 with python scripts.
  • Developed machine learning algorithm to predict how much a loanee earns per month based on some variables.
Software Developer
Contract
Jun 2019 - Aug 2019
Terragon group Company
Arts and Entertainment Industry
Project: Data Analyst
  • Data Analytics
  • Power BI
  • Microsoft Excel
  • Tableau
  • MySQL
  • Daily analysis and reporting across all live campaigns using my data analytics skills.
  • Proficient use of Microsoft Excel to seamlessly perform my duties.
  • Data gathering for marketing campaigns using MySQL.
  • Created a marketing dashboard with Tableau.
  • Plotted graphs and charts with Power BI for easy reporting and visualisation of campaign performance.
Qualifications
Courses
Data Engineering
May 2020 - May 2020
Udacity
  • Apache Spark
  • AWS ElasticMapReduce
  • AWS ECR
  • Data Engineering
Natural language processing specialisation
Sep 2020 - Dec 2020
Cousera
  • Natural language processing
  • Twitter APIs
  • Google NLP API
  • Machine learning
  • Python
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