MindBridge is the global leader in AI-powered financial risk intelligence. Our platform, MindBridge AI™ is enabling finance and audit professionals to build the AI-powered finance department of the future. With over 120 billion financial transactions analyzed with MindBridge’s AI, we set the standard for innovation, scalability, and customer satisfaction.
At MindBridge, we’re driven by innovation and excellence, united as a team to revolutionize financial integrity. Here, your ideas matter, and your efforts make a meaningful impact. If you’re passionate about using AI to drive positive change, MindBridge is the perfect fit. What distinguishes us is our unwavering commitment to our values: Innovation, Collaboration, and Integrity. These principles foster a vibrant workplace culture, where appreciation and a strong sense of community flourish.

DESIRED SKILLS & EXPERIENCE:

• Strong background in data science, statistics, or applied machine learning.
• Proven experience working in client-facing or stakeholder-heavy roles (consulting, delivery, or internal advisory).
• Hands-on skills in Python, SQL, and ML frameworks (PyTorch, TensorFlow, RAPIDS is a plus).
• Ability to move fluidly between technical modeling and business storytelling.
• Excellent communication skills with a collaborative mindset.
• Graduate degree (Master’s or PhD) in Computer Science, Statistics, Mathematics, or related field.
• Experience with modern ML methods such as deep learning, transformers, or generative models.
• Familiarity with agile methods for research and prototyping.

Requirements contingent on employment:

• Fulfill requirements necessary to obtain full background check.

ABOUT THE ROLE:

We’re seeking an Applied Data Scientist to join our centralized Data Science team. This role blends technical expertise with consulting skills—you’ll build models and algorithms while working directly with clients and stakeholders to frame problems, translate insights, and deliver measurable business impact.
You’ll rotate between client delivery projects, innovation sprints, and core research, staying connected to both cutting-edge data science and real-world applications.

KEY RESPONSIBILITIES:

Client Delivery & Consulting:

• Engage with clients to understand their business challenges and translate them into data science problems.
• Present insights, models, and recommendations clearly to both technical and non-technical audiences.
• Act as the bridge between clients, business teams, and technical experts.

Applied Data Science:

• Develop and implement machine learning models, statistical analyses, and advanced data workflows.
• Partner with research and prototyping teams to adapt novel algorithms for practical use cases.
• Validate and iterate solutions to ensure they are robust, scalable, and impactful.

Collaboration & Leadership:

• Contribute to a culture of knowledge sharing through peer mentorship, workshops, and technical write-ups.
• Support the team’s innovation agenda by testing and applying new AI/ML techniques.