Data Scientist / ML Engineer

Data Scientist / ML Engineer | RemoteWLB
Work arrangement
Fully remote
Employment
Full-time
Work & location
Remote policy
Themis is a remote-first team. Engineering operates with flexible working hours and supports asynchronous work, but all engineers are expected to maintain meaningful daily overlap with our core collaboration hours of approximately 11:00 AM–4:00 PM ET for standups, pairing, code review, and time-sensitive work.
Time zones
Daily overlap with 11:00 AM–4:00 PM ET
Experience & eligibility
Experience
Experience taking models or data products from prototype to production
Inside the role
Qualifications
Machine learning fundamentals Python Data/ML libraries (pandas, scikit-learn, PyTorch, TensorFlow) Production ML deployment experience SQL Experiment design and evaluation metrics
Themis is hiring a Data Scientist / ML Engineer to build and deploy machine learning and LLM-powered features for governance, risk, and compliance workflows. The role involves the full model lifecycle from problem framing to production monitoring within a regulated financial services context.
Remote scope
None
Time zones
Daily overlap with 11:00 AM–4:00 PM ET
What you need
– Machine learning fundamentals
– Python
– Data/ML libraries (pandas, scikit-learn, PyTorch, TensorFlow)
– Production ML deployment experience
– SQL
– Experiment design and evaluation metrics
What you will own
– Frame ambiguous compliance and risk problems as well-defined data and modeling tasks
– Build, evaluate, and iterate on machine learning models and LLM-powered features
– Design experiments and define metrics that measure real impact on customer workflows
– Build and maintain data and ML pipelines for training, inference, and monitoring
– Deploy models and AI features into production and monitor their performance
– Collaborate with engineering to integrate models into the Themis platform reliably and at scale
Core skills
PythonMachine LearningSQLLLMsMLOpsStatisticsData Pipelines
Remote policyThemis is a remote-first team. Engineering operates with flexible working hours and supports asynchronous work, but all engineers are expected to maintain meaningful daily overlap with our core collaboration hours of approximately 11:00 AM–4:00 PM ET for standups, pairing, code review, and time-sensitive work.
pythonmachine learningsqlllms
About Themis
Themis is a collaborative governance, risk, and compliance platform helping banks, credit unions, and fintechs streamline oversight, strengthen compliance programs, and move faster with confidence.
Our customers operate in highly regulated environments where strong governance, risk management, and compliance practices are critical. We partner closely with financial institutions and fintechs to help them build scalable, effective oversight programs, strengthen third-party oversight, and navigate an increasingly complex regulatory landscape.
At Themis, we believe great companies are built through partnership, expertise, ownership, and execution. We’re looking for team members who are excited to solve meaningful problems, build trusted relationships, and help shape the future of governance, risk, and compliance.
About the Role
We’re looking for a Data Scientist / ML Engineer to help Themis turn data into intelligence that makes governance, risk, and compliance faster, smarter, and more reliable for our customers.
In this role you’ll work across the full lifecycle, from framing problems and exploring data to building, deploying, and monitoring models and AI-powered features in production. You’ll help us apply machine learning and large language models to real compliance workflows where accuracy, explainability, and trust are non-negotiable.
The ideal candidate is equally comfortable in a notebook and in a production codebase. You care about rigor and measurable impact, you communicate findings clearly to non-technical stakeholders, and you are thoughtful about deploying AI responsibly in a regulated domain.
Working Hours & Availability
Themis is a remote-first team. Engineering operates with flexible working hours and supports asynchronous work, but all engineers are expected to maintain meaningful daily overlap with our core collaboration hours of approximately 11:00 AM–4:00 PM ET for standups, pairing, code review, and time-sensitive work.
This role does not carry a regular on-call requirement, though occasional availability outside of standard business hours may be needed to support production model issues or time-sensitive launches.
We support flexibility where possible, but regular or extended blocks of unavailable time during core hours should be discussed and aligned in advance.
What You’ll Do
Modeling & Experimentation
– Frame ambiguous compliance and risk problems as well-defined data and modeling tasks
– Build, evaluate, and iterate on machine learning models and LLM-powered features
– Design experiments and define metrics that measure real impact on customer workflows
– Apply rigorous evaluation, including accuracy, explainability, and bias considerations appropriate to a regulated domain
Production ML & Engineering
– Build and maintain data and ML pipelines for training, inference, and monitoring
– Deploy models and AI features into production and monitor their performance over time
– Collaborate with engineering to integrate models into the Themis platform reliably and at scale
– Implement guardrails, evaluation harnesses, and monitoring for AI-powered features
Data & Insight
– Explore and prepare data, build features, and ensure data quality and integrity
– Translate data and model findings into clear recommendations for product and leadership
– Partner with Product to identify high-value opportunities for ML and AI
Required Qualifications
– Strong foundation in machine learning, statistics, and data science fundamentals
– Proficiency in Python and common data and ML libraries (e.g., pandas, scikit-learn, PyTorch, or TensorFlow)
– Experience taking models or data products from prototype to production
– Experience with SQL and working with real-world, messy data
– Ability to design experiments, define metrics, and evaluate models rigorously
– Strong communication skills and the ability to explain technical work to non-technical stakeholders
– Ability to manage ambiguity and own problems end to end
Preferred Qualifications
– Experience building with large language models, retrieval-augmented generation, or modern AI tooling
– Experience deploying and monitoring ML in production (MLOps)
– Experience in financial services, compliance, risk, fraud, or other regulated or high-stakes domains
– Familiarity with cloud data and ML platforms (e.g., AWS, GCP, or Azure)
– Experience working in a startup or high-growth company
What We Value
The people who thrive at Themis tend to share a common set of characteristics:
Hunger & Ownership
We act like owners. We take initiative, spot gaps, and drive results for both our customers and the company.
Radical Accountability
We own outcomes without blame or excuses. We communicate early, learn from mistakes, and stay focused on solutions.
Problem Solver Mentality
We are builders, not blockers. We bring recommendations, options, and next steps, not just problems.
Mission & Customer Focus
Our customers trust us with critical compliance work. We take that seriously, advocate for their needs, and look for ways to deliver real value.
Low Ego, High Impact
We care more about solving problems than getting credit. We stay collaborative, coachable, and ready to jump in wherever needed.
Adaptability & Resilience
We stay flexible and steady through change. When priorities shift or challenges come up, we keep moving forward.
Curiosity & Continuous Learning
We are excited to learn. We dig into how the product works, investigate issues, use AI and automation thoughtfully, and keep growing into trusted experts.
Why Join Themis?
At Themis, you’ll apply data and AI to problems where getting it right really matters. You’ll own meaningful work end to end, ship to production, and help define how a growing company uses machine learning responsibly.
If you’re excited to build intelligent features that customers depend on and to do it thoughtfully in a regulated space, we’d love to hear from you.