Data Scientist III

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.

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 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.

• →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.
• →Plan and execute end-to-end data science projects, from data collection and exploration through model development, deployment, and intelligent decision-making.
• →Engage with stakeholders to identify and define the scope of challenges and propose data-powered solutions.
• →Staying informed with new frameworks and technological advances to increase Mozn's efficiency and productivity.
• →Deploy and maintain AI and machine learning models across on-prem, cloud, and hybrid environments.

• 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.
• Programming experience over three years, 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.
• Experience in SQL or NoSQL is preferred.
• Familiarity with big data technologies, such as Spark.
• Experience in deep learning frameworks, such as PyTorch.
• Familiarity with containerization frameworks, such as Docker.
• Experience deploying, operating, and managing applications or services in cloud environments, whether related to AI/ML or broader software workloads.