At a Glance
- Tasks: Join our team to leverage AI in transforming financial risk intelligence.
- Company: MindBridge, a leader in AI-powered financial solutions.
- Benefits: Competitive salary, flexible work options, health benefits, and wellness programs.
- Other info: Diverse and inclusive workplace with excellent career growth opportunities.
- Why this job: Make a real impact in finance while working with cutting-edge technology.
- Qualifications: 5+ years in data science, strong SQL and Python skills required.
The predicted salary is between 130000 - 155000 $ per year.
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.
Role Overview
We are looking for a Senior Data Science Engineer to provide applied data science expertise within our Success Engineering team, helping customers maximize the value of MindBridge’s control points and ensembles. You will configure and tune existing models, assess their application to customer data, investigate model behaviour and results, and translate complex findings into practical solutions. Working primarily post-launch, you will partner closely with Success Engineering, Product, Engineering, and AI/ML teams to solve complex customer needs within MindBridge’s existing capabilities.
What You Will Do
- Maintain deep working knowledge of MindBridge's core detection methodologies: scoring logic, risk indicators, and how ensembles combine individual control points into a single output.
- Serve as the go-to technical resource within Success Engineering for questions about how a model or ensemble actually works.
- Maintain an active, ongoing working relationship with Product, Engineering, and AI/ML teams to stay current on model changes, known limitations, and upcoming capability shifts.
- Use that relationship to bring well-informed, technically grounded context back to Product/Engineering when a configurability gap is identified.
- Develop and maintain authoritative understanding of how, why, and to what extent MindBridge's core models and ensembles can be configured.
- Map a customer's stated business value requirement onto the specific configuration options actually available.
- Evaluate customer requests to add, modify, or reconfigure a control point or ensemble, and determine whether it is feasible with existing product capability and the customer's available data.
- Translate model and ensemble behavior into language finance, audit, and compliance stakeholders can act on.
- Distinguish clearly between a configuration question and a request that requires new product capability.
- Convert recurring model and configuration questions into FAQs, decision guides, and training material for Success Engineers, Success Engineering Architects, and Delivery Services.
- Act as an internal subject-matter-expert resource for Solutions Architects and Data Engineers.
Required Qualifications
- 5+ years of applied experience in data science, analytics engineering, or a closely related technical discipline.
- Working knowledge of the statistical and machine learning techniques used in anomaly and risk detection.
- Strong SQL, Python and data literacy.
- Demonstrated ability to translate technical model behavior into terms a non-technical stakeholder can act on.
- Direct experience working with enterprise customers on technical questions.
- Credible enough with model internals and engineering constraints to partner directly with Engineering and AI/ML teams.
Preferred Qualifications
- Experience in audit, internal controls, financial risk, or fraud analytics.
- Familiarity with explainability and interpretability expectations in regulated or audit-facing environments.
- Experience producing enablement content for internal technical teams.
- Prior experience in a dedicated post-implementation optimization function.
- Background in ML engineering, applied statistics, or a related technical field.
Requirements contingent on employment
Fulfill requirements necessary to obtain full background check.
Pay Range
The expected base salary range for this position is $130,000 to $155,000 and may be eligible for bonus awards.
Why You’ll Love Being Part of Our Team:
- Competitive Compensation and Equity
- Flexible Work – Hybrid or Remote
- Comprehensive health benefits and wellness programs
- Unplug and recharge - 4 company-wide digital detox days annually
Equal Opportunity at MindBridge
At the heart of our global success lies commitment to diversity and inclusion. We rigorously enforce an equal opportunity policy in all aspects of employment, championing merit and qualifications as our benchmarks.
MindBridge is a proud equal opportunity employer, embracing applicants of all backgrounds without regard to race, nationality, religion, gender, disability, or any other factors.
At MindBridge, we are committed to providing an accessible candidate experience. If you require accommodations during the interview process or beyond, please inform us.
Please be advised that we may use AI tools in the processing of your application.
Senior Data Engineer employer: MindBridge
MindBridge is an exceptional employer that fosters a collaborative and innovative work culture, allowing Senior Data Science Engineers to thrive in a remote environment while contributing to impactful projects. With a strong emphasis on employee growth, MindBridge offers opportunities for professional development and equity participation, making it a rewarding place for those looking to make a meaningful impact in the field of data science.