As the Data Strategy and Operations Manager at Abnormal AI, you will own our go-to-market data quality strategy and serve as the steward of data across Salesforce and the systems around it. You will design the processes, controls, and intelligent workflows that keep data accurate, enriched, and trusted at scale, so Sales, Marketing, Customer Success, and Finance can give executive leadership reliable metrics. You will decide where AI agents and automation take over repetitive data work and where human judgment still matters, and partner with cross-functional teams to evaluate system changes that affect our data programs.
Who you are- Data obsessed and just as obsessed with removing manual work, with a habit of automating any process that relies on fixing records by hand
- Curious about AI and a daily user, with experience shipping workflows with LLMs, agents, or AI-assisted tooling, and able to tell a useful application from a demo
- Eager to build and shape a program rather than only maintain one, and able to create systems that hold up at global scale
- Highly analytical, able to see the big picture and spot trends and gaps, then zoom in with practical, specific recommendations
- Steady when juggling multiple priorities in a constantly changing environment
- A good teammate, dedicated to the mission, who likes to have fun along the way
- Set the data governance strategy, standards, ownership model, and source-of-truth hierarchy for GTM data across Salesforce and connected systems
- Establish policies, access controls, and field-level definitions, including record creation and deprecation rules, and monitor adherence
- Ensure compliance and security of our data, and flag risks to IT, security, and leadership
- Replace high-volume manual tasks (deduplication, enrichment, account matching, hierarchy mapping, routing, anomaly review) with automated and AI-assisted workflows
- Design and maintain AI agents and LLM-powered workflows that classify, enrich, validate, and remediate data, with guardrails, human review points, and accuracy measurement
- Build automated data quality monitoring that detects issues early, alerts the right owner, and fixes them without human intervention where appropriate
- Evaluate and select AI, enrichment, and automation tooling, run pilots, and measure impact through time saved, accuracy gains, and coverage
- Own the enrichment strategy and keep account firmographics accurate: hierarchies, employee count, location, industry, and Fortune ranking
- Act as the subject matter expert for Business Ops, Marketing Ops, Customer Success, and Finance, run a defined feedback intake process, and support consistent reporting and dashboards
- Manage a portfolio of data quality and automation projects with clear priorities, owners, and outcomes
- 5+ years in Sales Operations, Data Operations, or a similar analytical or systems role
- Hands-on experience building automation with AI or LLM tools (agents, prompt-driven workflows, AI-assisted enrichment), with shipped examples you can easily share
- Strong understanding of data lifecycle management, data modeling, master data management, and requirements gathering
- Demonstrated understanding of Salesforce automation, including Flow and validation rules, and experience working closely with admins
- Experience implementing and managing data and enrichment tools, including AI-native tools such as Clay, Kernel, Starbridge, and Onfire
- Proficiency in Excel
- Track record of leading data management projects from idea to result
- Sound judgment about where AI is reliable and where it needs controls for privacy, security, and accuracy
- Detail oriented, self-motivated, proactive, and quick to learn new tools
- Strong written and verbal communication skills, including explaining technical and AI concepts to non-technical partners
- Preferred: experience with workflow automation or integration platforms (such as Workato or Zapier), modern data stack tools (such as Snowflake or dbt), SQL, and a high-growth SaaS or security company
#LI-EM3
Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location.
In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package.
A note on AI in our process:
Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards.
Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.
Similar Jobs
What you need to know about the NYC Tech Scene
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
