AI Data Specialist

Company Overview

We are the better way to work in finance. As private equitys 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 where we support the office of the CFO to drive end-to-end value creation.

If you crave challenging work and are looking togrow come solvecomplexissues alongside1400 finance & technology experts ina supportive collaborativeenvironment.

Backedby premier private equity firms and headquarteredin New York with 10officesaroundtheglobe we are a high-growth entrepreneurial firmlookingforpeoplewhowantto be part of buildingsomethinggreat. Come make your mark.

Data & Analytics

Accordions Data & Analytics (D&A) team offers cutting-edge intelligent solutions to a global clientele leveraging a blend of domain knowledge sophisticated technology tools and deep analytics capabilities to tackle complex business challenges.

We partner with Private Equity clients and their Portfolio Companies across diverse sectors including Retail CPG Healthcare Media & Entertainment Technology and Logistics.

This role can be based in any of our US office locations and is a hybrid role with the flexibility to work remotely 2 days a week. Ideal candidates should be local to the desired location.

This position is not eligible for immigration sponsorship.

Accordion Intelligence Lab

The AI Lab is composed of leading software and AI engineers designing agentic-AI solutions ahead of the market. Our group builds and operationalizes the AI systems that power Accordions consulting capabilities from agentic architectures and RAG pipelines to evaluation frameworks and production observability.

The Lab works closely with practice leaders to translate research findings into scalable reliable tools that advance Accordions AI-driven value creation work for PE clients and their portfolio companies.

About the Role

Were looking for a Data Specialist to join one of Accordions AI-augmented delivery pods. These pods are purpose-built teams that combine AI engineering data science and product management to transform how PE-backed companies run finance and operations.

In this role you are the person who makes data work in practice. You move fluidly between messy source systems and production-ready pipelines and you do it fast. Youll work directly alongside AI engineers and product managers to scope data requirements diagnose quality issues and build the data foundations that AI systems depend on. Client-facing moments come with the territory. Youll need to ask sharp questions explain what youre seeing in plain language and earn trust quickly.

This is not a role for someone who needs clean handoffs and stable requirements. The data is complicated the timelines are short and the problems change. If that sounds like the environment where you do your best work this is the role.

What Youll Do

• Build and maintain the data pipelines models and integrations that AI systems depend on from raw source data to production-ready outputs
• Scope design and write custom ML models tailored to client problems from feature engineering through evaluation and deployment
• Explore unfamiliar datasets with speed and rigor: identify structure surface anomalies and form a clear point of view on what the data can and cant support
• Diagnose data quality issues quickly communicate their impact clearly and drive resolution without waiting to be asked
• Work directly alongside AI engineers and product managers to translate ambiguous client problems into reliable well-documented data products
• Run client working sessions on data (source system walkthroughs model findings quality assessments) and own the room when you do
• Tell the data story to non-technical audiences: in a chart in a slide in a meeting with a CFO who doesnt have time for jargon
• Navigate enterprise data environments fluently (ERP systems BI platforms financial data infrastructure) and get things done inside them
• Use AI tools to move faster across the full scope of your work: exploration modeling documentation and client communication
• Travel to client site as needed

Success in the First 6 Months

• Own end-to-end data delivery on multiple AI engagements from initial source system assessment through production-ready pipelines
• Establish a reputation within your pod for being the person who finds the data problem before it becomes the teams problem
• Run direct client working sessions on data (scope quality or access) and leave the client confident in your read of the situation
• Demonstrate faster higher-quality output because of how you use AI tools not just that you use them

What Youll Bring

• Deep practical data skills across the full stack: SQL Python machine learning data modeling pipeline development and hands-on experience with messy real-world source systems
• Strong instincts for data quality: You find the problem quantify the impact and communicate what it means before anyone has to ask
• Experience working in fast-moving sprint-based environments where requirements shift and you still ship
• Comfort working directly with clients: Asking the right questions translating technical findings into plain language and building credibility quickly
• Background in finance or PE-adjacent environments: ERP systems FP&A data financial close processes or portfolio company data infrastructure
• Fluent with AI and ML workflows: Enough to understand what the engineers need from the data layer why it matters and the ability to teach what you know
• AI tools woven into how you work daily with demonstrably faster output to show for it
• Strong written communication: you can document a model write a findings summary produce compelling stories from messy data and draft a client-facing issue log clearly and quickly

This is a high-velocity environment. Sprints are short client expectations are high and we dont slow down between engagements. If youve spent time in large enterprise engineering organizations where velocity is constrained by process this will feel different.

The people who thrive here are those who find the pace energizing not exhausting. They ship fast because theyve internalized good judgment (not because they cut corners). They use AI tools to multiply their output communicate clearly with non-technical stakeholders and course-correct quickly when something isnt working.

The annual salary for this role ranges from: $144500 to $230000 USD significant bonus benefits. Actual compensation packages are determined by evaluating a wide array of factors unique to each candidate including but not limited to geographic location skill set years and depth of experience education certifications cost of labor and internal equity.

Accordion is an Equal Opportunity Employer. We are committed to building a team that represents a variety of backgrounds perspectives and skills. We do not discriminate on the basis of race color religion marital status age national origin ancestry physical or mental disability medical condition pregnancy genetic information gender sexual orientation gender identity or expression veteran status or any other status protected under federal state or local law.

Please note that as per Accordion policy we do not accept unsolicited resumes from third-party recruiters unless such recruiters are engaged to provide candidates for a specified opening and in alignment with our inclusive diversity values. Any employment agency person or entity that submits an unsolicited resume does so with the understanding that Accordion will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency person or entity.

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