Data Scientist

Mozn is a rapidly growing technology firm revolutionising the field of Artificial Intelligence and Data Science headquartered in Riyadh, Saudi Arabia and it’s working to realise Vision 2030 with a proven track record of excellence in supporting and growing the tech ecosystem in Saudi Arabia and the GCC region. Mozn is the trusted AI technology partner for some of the largest government organizations, as well as many large corporations and startups.

We are in an exciting stage of scaling the company to provide AI-powered products and solutions both locally and globally that ensure the growth and prosperity of our digital humanity. It is an exciting time to work in the field of AI to create a long-lasting impact.

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.

**As a Data Scientist, your daily workload might include**:

- Work with Mozn’s Leadership, Product, Business, and Engineering teams to enable insights and intelligent decision-making across products and projects.
- Work with large and complex data sets to solve difficult, non-routine analysis problems using a combination of statistical and machine learning approaches.
- Develop quality control and pre-processing tools for a variety of data streams.
- Communicate highly technical results and methods clearly, as well as interact with a wide variety of external clients.
- Staying informed about developments in Data Science and adjacent fields to ensure that modern yet optimal approaches are applied to the relevant problems.
- Performs other related duties as required.

**Requirements**:

- Bachelor’s degree in Statistics, Mathematics, Computer Science, or other scientific fields.
- 0-2 years of relevant work experience (e.g. as a statistician/data scientist).
- Applied experience with machine learning and data science.
- Experience articulating business questions and using mathematical techniques to arrive at an answer using data and models.
- Demonstrated skills in selecting the right statistical/machine learning tool given a data analysis problem.
- Demonstrated skills in data visualization techniques.
- Demonstrated experience in extracting actionable insight from quantitative data.
- Excellent business and technical communication skills, and an ability to independently prioritize your workloads to achieve a common goal.
- A strong bias to action — you are excited to learn and do new things as required to create tangible impact.
- General programming proficiency, with an emphasis on Python/R/SAS/SQL.
- Knowledge of version control and peer review systems/workflows.
- Knowledge deploying algorithmic systems in an operational environment.
- General knowledge of software development frameworks, and how they interact across the stack.
- Comfort with command-line interfaces, as well as working familiarity with cloud computing resources.

**Benefits**

**We think you'll enjoy working at Mozn. Here's why**:
- 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.