Sr. Data Scientist - Prompt Engineering

HKA Global•Washington, DC

21h•$120,000 - $150,000

About The Position

HKA is seeking a Senior Data Scientist to take a hands-on, delivery-focused role applying prompt engineering, artificial intelligence (AI), machine learning (ML), and process automation to complex, real-world data problems. This role is vendor-neutral and emphasizes designing AI-driven workflows, providing structured context to large language models (LLMs), and driving measurable efficiency gains. While HKA currently uses Jylo as an embedded AI tool, prior experience with this platform is not required and can be learned quickly. Success in this role depends on strong fundamentals in applied data science and the ability to translate legal, technical, and commercial context into effective AI-enabled solutions — rather than deep expertise in any single product or platform.

Requirements

5+ years of hands‑on experience in applied data science, machine learning, or advanced analytics roles, with direct responsibility for delivery (not research‑only)
Experience in Professional Services consulting, expert advisory, forensic, legal, or investigative environments, where outputs must be accurate, explainable, and defensible
Proven experience working with large, unstructured, text‑heavy datasets (e.g., document review, investigations, disputes, or similar use cases)
Practical experience applying LLMs, NLP, or text analytics to real-world workflows such as document classification, relevance review, summarization, or issue tagging
Hands‑on experience designing and refining automation or ML pipelines, from prototype through production use
Strong Python‑based data science skills with the ability to work quickly, iterate, and troubleshoot independently
A pragmatic, delivery‑focused mindset with the ability to translate ambiguous legal or business problems into structured, AI‑enabled solutions

Nice To Haves

Expertise with Jylo strongly preferred, not required.

Responsibilities

Lead prompt engineering as a core capability within HKA
Design, test, and refine structured prompt playbooks aligned to litigation, arbitration, and investigative use cases
Provide legal, technical, and commercial context to LLMs to improve accuracy, relevance, and defensibility of outputs
Apply AI and ML techniques to large-scale document review in construction disputes, fraud investigations, and arbitration matters
Analyze document populations typically ranging from 150,000 to 250,000+ records
Reduce large datasets to high‑value, defensible subsets for Partner and expert review
Design and implement AI‑enabled data cleansing, normalization, and de‑duplication pipelines
Improve speed and quality of relevance classification and issue tagging
Reduce manual effort through intelligent automation while maintaining auditability and quality controls
Identify manual, repeatable processes suitable for automation across delivery teams
Support opportunity‑to‑cash and delivery workflows through RPA and process automation initiatives
Rapidly prototype and iterate on automation solutions in a developing, evolving environment
Operate with a tool‑agnostic mindset, focusing on fit-for-purpose solutions rather than specific vendors
Evaluate and recommend new AI, ML, or automation tools where they add clear value
Contribute to shaping HKA’s broader AI, data, and automation roadmap