Data Scientist

Location: Riyadh, Saudi Arabia

Department: Solutions

About the role

We are searching for a strategic and inquisitive Data Scientist. As a member of Mozn's Data Science team, you will work with cross-disciplinary teams to identify the problems to be solved, specify the problems in mathematical and statistical terms, scope out the project/product in collaboration with your team and external stakeholders, and then go about answering the identified questions. You find insights that spur teams and stakeholders to improve their business/product and drive value for internal and external stakeholders.

What you’ll do

• Work with cross-functional teammates from engineering, products, business, and marketing to deliver data-powered solutions.
• Communicate highly technical results and methods clearly to a wide variety of external clients.
• Analyze and extract insights from multiple and complex datasets through regression analysis, hypothesis testing, and other machine learning techniques.
• Develop and apply new machine learning techniques to ensure modern yet optimal approaches are applied to Mozn's solutions.
• Develop data pipelines and ingestion engines for Natural Language Understanding and/or Risk Management; as well as contribute to current engines at Mozn.
• Engage with stakeholders to identify and define the scope of challenges and propose data-powered solutions.
• Plan and execute solutions' development from data gathering to intelligent decision making.
• Staying informed with new frameworks and technological advances to increase Mozn's efficiency and productivity.

Qualifications

• B.S. or M.S. in Computer Science, Statistics, Mathematics or similar quantitative fields.
• 3-5 years of Relevant experience as a data scientist, or similar fields that require developing ML/AI models. Over 2 years for B.S. degree and over 1 year for M.S.
• Programming experience over two years in object oriented programming, including data manipulation using Python or other languages.
• Good understanding of statistics and probability, such as Bayesian methods and conditional probability.
• Applied experience in machine learning, such as conducting model experiments.
• Experience in version control systems, such as Git, GitHub.
• Programming experience in SQL or NoSQL is preferred.
• Familiarity with big data technologies, such as Spark.
• Experience in deep learning frameworks, such as PyTorch.
• Expertise in Natural Language Understanding and/or Risk Management applications.
• Familiarity with containerization frameworks, such as Docker.
• Research experience in optimization and natural language processing (NLP).

Benefits

• You will be at the forefront of an exciting time for the Middle East, joining a high-growth rocket-ship in an exciting space.
• You will be given a lot of responsibility and trust. We believe that the best results come when the people responsible for a function are given the freedom to do what they think is best.
• The fundamentals will be taken care of: competitive compensation, top-tier health insurance, and an enabling culture so that you can focus on what you do best
• You will enjoy a fun and dynamic workplace working alongside some of the greatest minds in AI.
• We believe strength lies in difference, embracing all for who they are and empowered to be the best version of themselves.

About the Company

About Mozn

MOZN is a leading Enterprise AI company enabling organizations to make informed decisions in two critical domains: Financial Crime Prevention and Enterprise Knowledge Intelligence.

We’re a diverse, collaborative team of innovators united by a shared purpose: to build AI that delivers tangible business value, builds trust, and empowers people and organizations with augmented intelligence. Our culture is built on the relentless pursuit of excellence and meaningful impact.

If you’re passionate about working alongside exceptional talent on world-class AI, and you want the autonomy and runway to do the best work of your career, join us in shaping the future of intelligent enterprises.