We use cookies to provide the best site experience.
Ok, don't show again
Citibot Case Study
How Citibot hired a Machine Learning Engineer.
Challenge
Citibot is a seed-stage company implementing intelligent chatbots for cities and states. The initial intention was to hire two interns. A Machine Learning Engineer for product development and a Javascript Developer to onboard new clients.
After further consideration, they realised they wouldn't have onboarding bandwidth for two interns. However, both work areas were essential for them. Therefore, they decided to find one individual that could cover both roles.
Finding a profile that combines an ML engineer and a full-stack developer was pretty challenging. Usually, ML engineers are familiar with the Python language, and their interests may not align with the fundamental role requirement.
Solution
Turing Talent and Citibot agreed to prioritise finding someone with ML skills and ramp up the individual on Javascript. Therefore, it was vital to find an individual with strong problem-solving skills and self-initiative.
Even with such a challenging requirement, we shortlisted a few candidates. After interviewing, Citibot narrowed it down to 2 finalists. Through our mediation, an offer was agreed with Aanu.
Aanu is completing a Master in Data Science and AI. Before that, he had two years of software development experience in a financial institution. He implemented a chatbot using Python during that time, which was a bonus point for Citibot.
Citibot is a seed-stage company implementing intelligent chatbots for cities and states. The initial intention was to hire two interns. A Machine Learning Engineer for product development and a Javascript Developer to onboard new clients.
After further consideration, they realised they wouldn't have onboarding bandwidth for two interns. However, both work areas were essential for them. Therefore, they decided to find one individual that could cover both roles.
Finding a profile that combines an ML engineer and a full-stack developer was pretty challenging. Usually, ML engineers are familiar with the Python language, and their interests may not align with the fundamental role requirement.
Solution
Turing Talent and Citibot agreed to prioritise finding someone with ML skills and ramp up the individual on Javascript. Therefore, it was vital to find an individual with strong problem-solving skills and self-initiative.
Even with such a challenging requirement, we shortlisted a few candidates. After interviewing, Citibot narrowed it down to 2 finalists. Through our mediation, an offer was agreed with Aanu.
Aanu is completing a Master in Data Science and AI. Before that, he had two years of software development experience in a financial institution. He implemented a chatbot using Python during that time, which was a bonus point for Citibot.
Results
As a result, Citibot valued his combination of technical skills. Moreover, his drive demonstrated during the interview gave the team confidence that he'd pick up Javascript quickly. To complement that, Citibot's team compiled several Youtube videos and resources for him to complete and ramp up on Javascript.
So far, Aanu has worked on:
Technologies used: Python, JavaScript, Svelte, Redux Bundler.
"This was our first experience trying to find an intern through a dedicated company. It was a lot easier that we would've thought. Everyone was so professional, kind and just willing to work with us."
- Alexandria Cottingham, Director of Marketing and Communications
You found this case study interesting? Click here for more.
As a result, Citibot valued his combination of technical skills. Moreover, his drive demonstrated during the interview gave the team confidence that he'd pick up Javascript quickly. To complement that, Citibot's team compiled several Youtube videos and resources for him to complete and ramp up on Javascript.
So far, Aanu has worked on:
- Developed a notification functionality on the website
- Enhance response to users by using web scraping.
- Development of WebChat 2.0.
- Research on sentiment analysis on Citibot communication.
Technologies used: Python, JavaScript, Svelte, Redux Bundler.
"This was our first experience trying to find an intern through a dedicated company. It was a lot easier that we would've thought. Everyone was so professional, kind and just willing to work with us."
- Alexandria Cottingham, Director of Marketing and Communications
You found this case study interesting? Click here for more.
Aanuoluwa Ayodeji
Machine Learning Engineer
Machine Learning Engineer
Master's Degree in Data Science and AI at University of Liverpool
© 2022 Turing Talent
Kemp House, 160 City Road, London, EC1V 2NX
hello@turingtalent.org
Kemp House, 160 City Road, London, EC1V 2NX
hello@turingtalent.org
About Us
