Senior Data Scientist

About the job

As a Senior Data Scientist, you will be a key part of Lean's mission to delight our clients by providing insights based on open banking data. You will be part of the engineering team tasked with that mission, partnering with product teams to identify potential opportunities and develop ML/AI models that solve real problems for clients. You will work hand-in-hand with the Data Engineering team to take models from the experimentation phase through to delivering high-quality and resilient insights in production. You will coach and mentor those around you to develop knowledge of ML/AI within Lean.

Who are we

Lean enables companies to seamlessly connect to their users' bank accounts to initiate real-time payments and retrieve their account information. Our products have garnered the trust of leading companies and enabled them to deliver powerful experiences when connected with a user's bank account, allowing users to perform prudent financial planning, get better rates on loans, transfer money to friends, and more, without compromising on privacy or security.

Some of Lean's clients include the likes of Tabby, Nayifat, Tamam, Circlys, and many more, making it the region's most valuable Open Banking platform. The company has now processed over a billion dollars, and its products are also connected with hundreds of thousands of accounts. Lean envisions a fully inclusive financial ecosystem that serves everyone, no matter where they bank or live in the MENA region.

Having recently announced our Series B raise ($67.5m) led by General Catalyst, we're broadening the scope of our Data & Insights division which spans our offices in Dubai, Riyadh, Pune and (remote) Europe.

Responsibilities

1. Design and implement ML/AI models to deliver insights such as transaction categorisation.

2. Work closely with clients and stakeholders to understand their needs and market context and map these into functional and non-functional requirements.

3. Perform data analysis and exploratory research for open banking data sets to uncover patterns and trends that inform improved or new models.

4. Design and implement approaches for feature extraction and labelling at scale, and for measuring model performance.

5. Collaborate with Data Engineering to ensure models are kept up-to-date and perform robustly at scale, with suitable automation and observability. Justify and advocate for improvements to data pipelines.

6. Stay up-to-date with the latest advancements in machine learning, NLP, Large Language Models (LLMs) and related fields, actively seeking opportunities to enhance knowledge and skills.

7. Enthuse and educate the wider team on the discipline of Data Science.

Minimum Qualifications

1. Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.

2. 5+ years of experience in ML/data science roles with a proven track record of building, delivering and operating ML-based insights in production.

3. Hands-on experience in deep learning frameworks such as TensorFlow or PyTorch.

4. Experienced and comfortable with collaborating closely with Data Engineering.

5. Knowledge of MLOps concepts, databases, data warehousing, data modeling techniques and data ETL pipelines.

6. Strong proficiency in relevant programming languages such as Python or R.

7. Strong written and verbal English and comfortable explaining data science concepts to non-technical audiences.

8. Fluent in Arabic.

Desired Qualifications

1. Payments / Open Banking experience.

2. A working knowledge of transformers.

3. Familiarity with CI/CD tools and cloud platforms like GCP, AWS or Azure.

NB. While we think the above experience could be important, we're keen to hear from people that believe they have valuable experience to bring to the role. If you identify with the team and mission, but not all of our requirements, then please still apply

Lean is the first regulated open banking and open finance company operating across the UAE and Saudi Arabia. Since 2019 we've been on a mission to become the pre-eminent A2A payments company in the Middle East - enabling our clients to seamlessly connect to their users' bank accounts to initiate real-time payments and retrieve account information. Our products have garnered the trust of some of the leading companies in the region, including the likes of Etisalat Group, Careem, Binance, Tabby, Tamara, Tawuniya, and more.

To date, Lean has processed billions of dollars, and our products have connected with hundreds of thousands of accounts across the region. We've recently announced our $67.5 million Series B funding round led by General Catalyst, following earlier investment from Sequoia Capital. This funding marks a major milestone for Lean and the financial ecosystem across the MENA region. At Lean, we're committed to driving the next generation of financial innovation by making financial data and payments more accessible and transparent for businesses and consumers alike.

To that end, we're always on the lookout for talented, driven, and entrepreneurial candidates to join us in our mission of enabling the next generation of financial innovation. If you're motivated by solving hard problems and leaving a lasting legacy while you're at it, Lean's where you need to be.

Not only do we offer competitive salaries, private healthcare, and flexible office hours, but we also insist that every member of the team hold a meaningful equity stake in the business to ensure long-term alignment. We'd love you to join us for this journey

Lean is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

When applying for a job at Lean Technologies, we will need to collect, use and share Personal Data about you with different members of our team during the application process. This may mean transferring your data to members of the team in one of our office locations worldwide outside of the country you are in. Please refer to our Privacy Notice on our website for more information about how we may use and store your Personal Data.