Data Scientist - GCP

Liminal is a global market intelligence and strategic advisory firm specializing in digital identity, financial crime and compliance, and IT security technology solutions across industries while also catering to the private equity and venture capital community. Founded in 2016, Liminal offers strategic and analytical services supporting executive decision-making at all product and business lifecycle stages. We advise some of the world’s most prominent business leaders, investors, and policymakers on building, acquiring, and investing in the next generation of solutions and technologies. We provide access to proprietary data and analysis, strategic frameworks, and integrated insights on the industry’s only market intelligence platform.

Every major company in the world has started focusing on the next generation of digital identity technologies as a necessity for continued growth and security. Our team works with a myriad of organizations, from Fortune 100s to startups, across industries including financial services, technology, telecommunications, and the P2P economy. At Liminal, we help businesses build solutions, execute strategies, invest intelligently, and connect with key decision-makers. We know that it’s in the sharing of discovery and insights that groundwork is laid, problems are solved, and entire sectors advance at the speed of light. Keeping information to ourselves delays progress for all. At Liminal, we don't just respond to the market; we define it.

About The Role

This role focuses on leveraging data science and AI methodologies to drive organizational efficiency and innovation across multiple departments. Reporting to the AI Solutions Architect and partnering closely with the Chief Innovation Officer, this Data Scientist will be instrumental in exploring and implementing AI solutions that improve research, marketing, advisory, and product functions. With a strong foundation in machine learning and practical experience with large language models (LLMs), the Data Scientist will work on projects from ideation to proof of concept (PoC) and support transitions to product teams when solutions reach maturity.

What You'll Do

• Cross-Department AI Solutions:
• Collaborate with various departments to understand needs, assess feasibility, and design AI-driven solutions to address organizational challenges.
• Partner with the Chief Innovation Officer to streamline workflows and introduce efficiency improvements through AI.
• Support the Chief Product Officer on transitioning mature projects, providing AI expertise to align product requirements and goals.
• Prompt Engineering and LLM Utilization:
• Develop, refine, and experiment with prompts, using methods such as Chain-of-Thought (CoT) reasoning to enhance model reasoning capabilities.
• Implement Retrieval-Augmented Generation (RAG) for contextual retrieval, optimizing LLM responses using internal data sources.
• Implement data science pipelines to fine-tune and evaluate LLMs on proprietary data, enhancing their accuracy and utility for internal applications.
• Utilize OpenAI and similar platforms to support customized AI models that align with organizational goals.
• Exploratory Data Science and Proof of Concept Development:
• Conduct exploratory analyses to identify patterns, generate insights, and provide recommendations.
• Build and test PoCs using tools like Jupyter notebooks and Streamlit to validate AI concepts, present findings, and gain buy-in from stakeholders.
• Translate business problems into data science workflows, adapting approaches based on project scope and data availability.
• Pipeline Development and Model Evaluation:
• Implement data science pipelines for data ingestion, processing, and analysis to support AI initiatives.
• Evaluate models for performance, iterating as necessary to ensure effectiveness and alignment with project requirements.
• Prepare models for transition to product development teams when projects progress beyond exploratory phases.
• Documentation and Compliance:
• Document findings, PoC designs, and technical workflows to maintain project transparency and enable smooth project handoffs.
• Maintain comprehensive documentation of code, models, and PoCs.
• Ensure compliance with organizational standards and data governance policies.
  

Qualifications

• Strong background in data science, machine learning, and a working knowledge of large language models (LLMs).
• Experience with machine learning frameworks (e.g., scikit-learn) and data processing libraries (e.g., pandas, numpy).
• Experience with prompt engineering and using platforms such as OpenAI to leverage LLMs for specific tasks.
• Proficiency in Python, with a focus on exploratory data science, proof of concept (PoC) development, and rapid prototyping (e.g., using notebooks and Streamlit).
• Proven ability to work in a cross-functional environment, collaborating effectively with technical and non-technical stakeholders.
• Excellent problem-solving and communication skills to translate business needs into data-driven insights.
• Strong analytical mindset, with a focus on evaluating, tuning, and iterating AI models in alignment with organizational goals.
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud) is desired.