interface.ai is the industry's-leading specialized AI provider for banks and credit unions, serving over 100 financial institutions. The company's integrated AI platform offers a unified banking experience through voice, chat, and employee-assisting solutions, enhanced by cutting-edge proprietary Generative AI.

Our mission is clear: to transform the banking experience so every consumer enjoys hyper-personalized, secure, and seamless interactions, while improving operational efficiencies and driving revenue growth.

interface.ai offers pre-trained, domain-specific AI solutions that are easy to integrate, scale, and manage, both in-branch and online. Combining this with deep industry expertise, interface.ai is the AI solution for banks and credit unions that want to deliver exceptional experiences and stay at the forefront of AI innovation.

About Interface.ai

interface.ai is the most advanced AI platform for financial institutions. We serve over 100 credit unions and community banks, enabling millions of intelligent conversations every day through voice, chat, and internal copilots.

As a fast-growing, AI-native company, data is at the heart of how we build, measure, and scale our products. From intelligent conversation design to customer automation analytics, we apply machine learning and statistical modeling to deliver real-time, measurable outcomes.

About The Role

We are seeking a Senior Data Scientist to lead the development of scalable, production-grade models and analytics systems that power core platform that our Products run on

This is a high-impact role where you'll work on problems at the intersection of language understanding, user behavior prediction, decision optimization, and platform-level intelligence. You will be embedded in product-driven teams, while also collaborating with infrastructure and research to shape the future of intelligence at interface.ai.

Key Responsibilities

Develop and deploy machine learning models for use cases like intent recognition, conversation scoring, outcome prediction, and next-best-action systems
Design and run A/B and multivariate experiments to validate hypotheses and measure product impact
Build real-time and batch inference pipelines in collaboration with engineering
Define, instrument, and maintain data pipelines for user interaction modeling, longitudinal engagement, and behavioral segmentation
Develop intelligence layers for customer-facing analytics products (e.g., AI explainability, task attribution, feature impact modeling)
Partner with product managers, engineers, and UX teams to define data-informed product features
Translate complex model outcomes into actionable insights for internal and external stakeholders
Stay current with research and best practices in Voice models, decision modeling, time-series analysis, and agentic AI architectures

What Success Looks Like

Within your first 6–12 months, you will:

Launch production-grade models that are actively used in product features or operations workflows
Define and validate key behavioral or predictive models that influence roadmap direction
Improve accuracy, performance, or interpretability of existing AI systems across voice and chat products
Drive measurable lift in engagement, resolution rate, or automation through data-driven product iterations
Collaborate across departments to establish trusted experimentation and measurement frameworks

Required

What You Bring

5+ years of experience in applied data science, including end-to-end model development and deployment
Strong knowledge of Python, R, SQL, and experience with ML libraries such and deep learning frameworks.
Experience with statistical testing, experiment design, and causal inference
Understanding of production ML pipelines and collaboration with data engineering teams
Experience with speech models, conversational systems, or classification models in user-facing applications
Strong product thinking—able to translate model insights into product impact and roadmap trade-offs

Preferred

Experience working in B2C environments especially in regulated industries (e.g., financial services, healthcare)
Exposure to retrieval-augmented generation (RAG), embedding-based search, or LLM evaluation frameworks
Familiarity with tools like Airflow, MLflow, dbt, or feature stores
Prior work in chatbots, IVRs, or user feedback systems

Why Join Us

Data science is central to our product innovation strategy
You’ll have a direct, measurable impact on customer outcomes and platform intelligence
You’ll work on real-world AI applications with scaled deployment and product visibility
You’ll collaborate with a cross-disciplinary team of engineers, designers, and product leaders moving at startup speed

At interface.ai, we are committed to providing an inclusive and welcoming environment for all employees and applicants. We celebrate diversity and believe it is critical to our success as a company. We do not discriminate on the basis of race, color, religion, national origin, age, sex, gender identity, gender expression, sexual orientation, marital status, veteran status, disability status, or any other legally protected status. All employment decisions at Interface.ai are based on business needs, job requirements, and individual qualifications. We strive to create a culture that values and respects each person's unique perspective and contributions. We encourage all qualified individuals to apply for employment opportunities with Interface.ai and are committed to ensuring that our hiring process is inclusive and accessible.