Responsible AI Data Scientist

Accordion•Chicago, NY

1d•$160,000 - $175,000•Hybrid

About The Position

We are the better way to work in finance. As private equity’s value creation partner, we sit at the heart of PE—where sponsors and CFOs meet. Through financial consulting rooted in data, technology, and AI, we help clients drive value—supporting the office of the CFO to drive end-to-end value creation. If you crave challenging work and are looking to grow, come solve complex issues alongside 1,400+ finance & technology experts in a supportive, collaborative environment, the Backed by premier private equity firms and headquartered in New York with 10 offices around the globe, we are a high-growth, entrepreneurial firm looking for people who want to be part of building something great. Come make your mark. About the role: We are seeking a Vice President, Responsible AI Data Scientist who combines technical expertise in Data Science and Machine Learning with a strong advisory lens to help drive trustworthy AI solution development across Accordion's practices. In this role, you will serve as an internal subject matter expert, embedding responsible AI principles and controls across the AI development lifecycle to drive validated, explainable, compliant, and auditable AI solutions. Drawing on your experience with AI policy, regulatory standards, and testing methodologies, you will translate governance requirements into actionable and testable playbooks that teams across the business can apply consistently. This position is critical to co-designing AI solutions with embedded Responsible AI practices aligned to Accordion's AI Governance principles. As Accordion scales AI capabilities across its practice areas, this role will provide the validation rigor and oversight needed to ensure we develop AI solutions our clients and firm can trust. This position must be based in our New York City or Chicago office and is a hybrid role with the flexibility to work remotely 2 days a week. This position is not eligible for immigration sponsorship.

Requirements

5+ years of hands-on experience in data and ML, including developing, deploying, and evaluating solutions using a range of skillsets (e.g., statistics, machine learning, NLP, data visualization)
Bachelor's degree in Computer Science, Data Science, Information Systems, Mathematics, Engineering, Statistics, or a related quantitative field
Proven technical experience in regulated or complex industries with demonstrated collaboration across Legal/Risk/Compliance, Security, and AI/ML engineering teams
Track record of operationalizing responsible AI through technical development frameworks, testing protocols, and quantitative evaluation that embed fairness, transparency, and accountability into production AI systems
Strong programming proficiency in Python, R, or similar languages, with experience in ML frameworks and responsible AI tooling
Understanding of AI and privacy regulations and standards — including EU AI Act, NIST AI RMF, GDPR, CCPA, and ISO 42001 — and the ability to translate regulatory mandates into technical controls
Exceptional communication skills with the ability to convey complex technical and regulatory considerations to non-technical stakeholders, including leadership and cross-functional teams

Nice To Haves

Advanced degree (Master's) in Computer Science, Data Science, Statistics, Information Systems, Engineering, or a related quantitative discipline
Consulting experience at a leading management or professional services firm
Direct experience working with Legal/Privacy/Compliance teams on AI, data governance, or emerging technology matters
Familiarity with responsible AI tooling, red teaming platforms, or model evaluation frameworks
Energized by ensuring AI systems that solve complex business challenges are built responsibly — with fairness, accuracy, transparency, explainability, and privacy by design embedded from the start
A cross-functional collaborator who navigates matrixed organizational dynamics, working seamlessly with Legal/Risk/Compliance, Technology/Engineering, and business teams to establish AI principles, governance playbooks, and technical roadmaps
A clear communicator who can translate AI governance concepts and technical risk findings into language that resonates with non-technical stakeholders and leadership
A proactive problem-solver who thrives on staying ahead of AI governance expectations and emerging regulations — and can turn frameworks into practical controls
An adaptive contributor who embraces the pace of consulting, working across diverse sectors and practice areas

Responsibilities

Governance & Technical Standards Translate AI governance, regulatory, and compliance requirements into testable operational Responsible AI playbooks with quantifiable standards for transparency, explainability, accuracy, fairness, privacy, and accountability — tailored to Accordion's AI solutions and business model
Develop frameworks and guidance supporting systematic evaluation, testing, and risk mitigation that enable auditability, lineage, and transparent decision records
Build evaluation frameworks that guide data scientists and engineering teams in developing, testing, and monitoring AI systems requirements; define mitigation strategies, detection methodologies, and acceptability thresholds
Develop and implement testing principles for bias detection, model robustness evaluation, privacy preservation, and AI/privacy regulation alignment across different AI architectures and data types
Establish benchmarks and governance processes aligned with industry standards (e.g., NIST AI RMF, EU AI Act, ISO 42001) that enable auditable AI transparency and explainability against applicable regulations and Accordion standards
Testing & Validation Collaborate with data science and engineering teams across our AI solution practices to embed responsible AI controls throughout the development lifecycle
Develop repeatable testing and validation playbooks and evaluation frameworks for use across practice areas
Pressure test AI solutions for accuracy, reliability, and trustworthiness, including output anomaly detection, logging, and observability mechanisms
Develop methods to produce model cards and support audit trails for outputs across Accordion's business practice pillars and Client solutions
Cross-Functional Advisory Act as the firm's internal subject matter expert on Responsible AI topics including algorithmic fairness, transparency, privacy preservation, safety protocols, and risk mitigation strategies across the AI lifecycle
Partner with Legal/Privacy/Risk, Technology, and D&A teams to translate regulatory requirements into actionable and measurable controls and governance structures
Collaborate with teams developing AI solutions on risk-informed design decisions — advising on model selection, testing approaches, and appropriate guardrails
Establish Responsible AI frameworks and operational playbooks that demonstrate alignment with evolving AI regulations (e.g., EU AI Act, GDPR, CCPA) and sector-specific requirements
Monitor emerging AI regulations, industry standards, and responsible AI methodologies — translating insights into actionable internal design guidance
Where applicable, support higher-risk or higher-profile engagements and AI product development where rigorous testing and evaluation of AI solutions is required