ML Engineer, Fintech

Optasia is a fully-integrated B2B2X financial technology platform covering scoring, financial decisioning, disbursement & collection. We provide a versatile AI Platform powering financial inclusion, delivering responsible financing decision-making and driving a superior business model & strong customer experience with presence in 30 Countries anchored by 7 Regional Offices.

We are seeking for enthusiastic professionals, with energy, who are results driven and have can-do attitude, who want to be part of a team of likeminded individuals who are delivering solutions in an innovative and exciting environment.

Data is at the core of Optasia growth plan and the ML Engineering team is a significant contributor to Optasia’s success and growth, achieved through data driven insights and decision making.  We are currently leveraging and ingesting data from multiple sources into our large-scale big data clusters and develop and run multiple analytical pipelines, over a state-of-the art big data technology stack. 
Machine Learning Engineers are significant contributors of the company’s data driven automated decision making and risk management. They have extensive experience with machine learning flows, and the development and deployment of advanced algorithms. They have the capability to (i) build ML flows , (ii) design and develop statistical and machine learning algorithms, and (iii) operationalize them in credit risk management, contributing to Optasia’s success. 

What you will do

Develop and deploy advanced, scalable and automated ML pipelines

Be comfortable navigating the following technology stack: Hadoop ecosystem, Airflow, Git, Docker, Jenkins Scala, Spark, Python, scripting (Bash/Python), SQL etc.

Write production-quality code for REST API services

Work closely with experienced Data Engineers, Solution Architects, ML engineers and System Administrators for the design, delivery and support of the company’s end-to-end ML workflows

Build and maintain CI/CD orchestration

Align coding standards to ensure proper code quality level

Keeping up with the latest in Data Science and Machine Learning tooling & communities

What you will bring

• Bachelor's or Master's degree in Electrical Engineering, Computer Science or Informatics
• 2+ years of industry experience with Applied Machine Learning, ML flows and Data Science
• Good knowledge in the core concepts of machine learning.
• Good knowledge in using the Python ecosystem (NumPy, Pandas) for data analysis
• Ability to efficiently search and understand the scientific literature of mathematical models, machine learning and AI
• Passion for learning, exploring and developing new models and machine learning and AI algorithms
• Ability to hit tight deadlines and work under pressure and strict attention to detail
• Cutting-edge technologies aware, with the ability to learn and adapt to new technologies

Optional requirements (will be considered a plus):

• Experience with big-data applications and tools (Apache Hadoop / PySpark or Scala framework) 
• Familiar with DevOps and CI/CD best practices (Git, Jenkins)
• Design and implement Airflow DAGs

Why you should apply

What we offer:
👟 Flexible remote working
💸 Competitive remuneration package
🏝 Extra day off on your birthday
💰 Performance-based bonus scheme
👩🏽‍⚕️ Comprehensive private healthcare insurance
📲 💻 All the tech gear you need to work smart

Optasia’s Perks:
🎌 Be a part of a multicultural working environment
🎯 Meet a very unique and promising business and industry
🌌 🌠 Gain insights for tomorrow market’s foreground
🎓 A solid career path within our working family is ready for you
📚 Continuous training and access to online training platforms

Optasia’s Values 🌟

#1 Drive to Thrive: Fully dedicated to evolving. We welcome all challenges and learning opportunities.
#2 Customer-First Mindset: We go above and beyond to meet our partners’ and clients’ expectations.
#3 Bridge the Gap: Knowledge is shared, information is exchanged and every opinion counts.
#4 Go-Getter Spirit: We are results oriented. We identify any shortcomings that hold us back and step up to do what’s needed.
#5 Together we will do it: We are committed to supporting one another and to understanding and respecting different perspectives, as we aim to reach our common goals.