Consultant – Compliance Data Science & AI
About The Position
Sia is recruiting a Data Scientist Consultant with a strong interest in risk, compliance, and regulatory topics. Reporting to Sia’s Data Science teams, the consultant supports clients’ operational teams and compliance departments in defining data needs, analyzing data, deploying data science algorithms and AI agents, and providing strategic decision support. Engagements span forward-deployed engineering; generative AI, machine learning, and statistics; strategic data analysis; data engineering and DevOps; and data transformation and acculturation. Example engagements include developing predictive compliance risk monitoring pipelines and dashboards, creating AI-powered regulatory intelligence systems that track regulatory changes and map obligations to internal policies and controls, and building machine-learning models for AML compliance workflows. The consultant also contributes to internal offerings and training, working groups, publications, and business development activities. The position partners with client leadership and technical teams to identify and analyze data, build predictive models and LLM-based applications, and communicate findings through presentations, dashboards, datasets, bots, and other mediums. GenAI solutions must address business needs and comply with applicable regulations and model licenses. Sia values in-person collaboration: consultants may work onsite at client locations as engagement needs require, and between engagements are expected to work from a Sia office or approved coworking location at least three days per week. Candidates should live within reasonable commuting distance of such a location.
Requirements
- Master’s degree, Engineering degree, or equivalent in Computer Science, Engineering, Data Science, or a related quantitative field.
- At least 2 years of experience as a Data Scientist or Data Analyst.
- Strong programming skills, particularly in Python and SQL.
- Proficiency with at least one major GenAI application framework, such as LangChain or LlamaIndex.
- Experience with a cloud platform such as AWS, Azure, or GCP.
- Knowledge of proprietary and open-source model ecosystems, such as OpenAI, Anthropic, Mistral AI, and Hugging Face.
- Excellent communication skills, including the ability to explain complex technical concepts simply.
Nice To Haves
- Experience building agentic AI systems.
- Good understanding of machine-learning techniques.
- Good understanding of statistical techniques and concepts.
- Experience with data visualization tools.
- Experience developing conversational AI systems or chatbots.
- Understanding of or experience with protocols and standards for connecting LLMs to external tools and databases, such as the Model Context Protocol (MCP).
- Experience deploying models at scale in production environments.
- Experience with regulatory obligations management, including analyzing and documenting requirements and maintaining regulatory obligations libraries.
- Experience designing and implementing operational controls and compliance frameworks.
- Experience leading risk and control self-assessments (RCSAs), thematic reviews, and control testing.
- Experience interpreting emerging regulatory trends and enforcement actions to inform compliance strategy.
- Experience developing and maintaining compliance best practices.
- Experience interpreting laws and regulations, assessing applicability, and mapping obligations to controls.
- Experience supporting risk and compliance transformation across first-line and second-line functions.
Responsibilities
- Partner with client leadership teams, engineers, program managers, and data analysts to understand data needs.
- Identify, acquire, process, and explore relevant data sources.
- Analyze structured and unstructured information to discover trends and patterns.
- Use data analytics and data science expertise to derive insights, and build predictive models and machine-learning algorithms.
- Design, build, fine-tune, and deploy LLM-based systems using models such as GPT, Claude, Gemini, Llama, and Mistral.
- Develop self-managed and API-based GenAI applications that meet business needs and comply with applicable regulations and model licenses.
- Design and optimize prompting strategies, including few-shot prompting, Chain/Tree-of-Thought, ReAct, self-reflection, and guardrails.
- Communicate findings through presentations, dashboards, datasets, bots, and other mediums.
- Propose solutions and strategies to business challenges.
- Collaborate with engineering and product development teams.
- Deliver models, algorithms, datasets, measurements, services, tools, and processes across a broad range of partners and projects.
- Contribute to developing or strengthening firm offerings through training, working groups, and internal and external materials.
- Contribute to publications, including sector blogs, studies, and press coverage.
- Support business development by helping define client needs and participating in sales activities.
Benefits
- Annual performance bonus.
- Medical, dental, and vision coverage.
- Company-paid life and AD&D insurance.
- Voluntary supplemental insurance and EAP.
- 401(k) with company match and immediate vesting.
- HSA and FSA options.
- College savings and student loan repayment programs.
- Paid parental leave.
- Generous PTO, nine company holidays, and one floating holiday.
- Cell phone stipend.
- Well-being and professional development programs.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
