Location: New York, NY (hybrid; 1+ days/week in NYC office)
Commitment: Part-time, 16–18 hours/week
Engagement type: Contract (1099)
Compensation: $7,000–$7,500/month retainer (equiv. ~$95–$110/hr) — DOE
About Origin
Origin is a creative tailor for brands and agencies seeking to transform conventional CTV campaigns into personally relevant, emotionally resonant moments at the household level. Blending human expertise with real-time data signals and objective-led logic models, we tailor the message based on the household, the context, and the moment - driving proven lifts in engagement, intent, and ROAS.
Founded by media veterans Stephen Strong and Fred Godfrey, Origin is guided by one mantra: to win the modern living room, your message needs to say, "we recognize you."
The Role
We're hiring an AI, Data & Analytics Lead to own three connected pillars at Origin: AI strategy and implementation, reporting and analytics, and data storage and infrastructure. You'll be the person who makes sure Origin runs on good information and modern tooling - and that every team has what they need to make faster, smarter decisions.
A flagship project from day one: rebuilding and expanding Origin's "brain" - our central, AI-powered repository that hosts and analyzes historical data from multiple sources through chat. The brain already exists in an earlier form, but we want to take it further: rebuild what isn't working, expand what data it ingests, sharpen how it retrieves and reasons, and make it genuinely indispensable to every team. Done well, the brain becomes a key piece of the creative logic engine that powers how Origin works internally.
This is a hands-on role. You'll spend more time in the work than in the abstract - building dashboards, piloting AI tools, cleaning up data systems, and coaching teammates. You'll report directly to leadership and have real latitude to make calls.
What You'll Do
Rebuild and Expand Origin's Brain (Flagship Project)
- Audit the current brain - what works, what doesn't, what's worth keeping vs. rebuilding
- Re-architect where needed: improve retrieval quality, expand the data sources it pulls from (campaigns, briefs, creative assets, performance results, financials, retrospectives, client history), and tighten the chat experience
- Establish stronger ingestion pipelines, taxonomy, and access controls
- Drive adoption - make the brain something teams actually reach for. Iterate based on real usage: what people ask, where it falls short, what to add next
- Set the roadmap for what the brain becomes over the next 6–12 months
AI Strategy & Implementation
- Sit with each team - creative, sales, ad ops, engineering, project management, ops - and map where AI could save time, improve quality, or unlock new capability
- Pilot tools, workflows, and integrations. Move quickly from "interesting" to "in use."
- Build prompt libraries, SOPs, and internal guides that turn one-off wins into repeatable practice
- Run lunch-and-learns, office hours, and 1:1 coaching so AI literacy becomes a baseline skill
Reporting & Analytics
- Own the company's reporting layer - define what gets measured, how it's surfaced, and who sees it
- Build and maintain dashboards that give leadership and team leads the visibility they need during - as well as after - a campaign ( performance, utilization, financials, pipeline)
- Partner with department leads to define the metrics that actually matter and replace gut-feel with data where it helps
Data Storage & Infrastructure
- Own how Origin stores, organizes, and accesses data across the company - from campaign assets and client data to operational and financial records
- Audit current systems, identify gaps and risks, and lead consolidation or migration where needed
- Establish sensible data hygiene, naming conventions, access controls, and retention policies
- Make sure our data foundation can support the AI, analytics, and brain work we want to do
Cross-cutting
- Develop clear guidelines around client data, IP, and quality standards - important in a creative and ad-tech context
- Track the model, tooling, and data landscape and translate what matters for Origin
Who You Are
- 4 - 6 years of experience spanning AI/automation, analytics, and data infrastructure - with depth in at least two of the three areas
- You're genuinely hands-on with current AI tools and modern data stacks - you've built dashboards, set up data pipelines, and shipped AI workflows
- Hands-on experience with RAG (retrieval-augmented generation), vector databases, or AI-powered knowledge management tools is a major plus
- Comfortable inheriting and improving existing systems - you can read someone else's work, figure out what's salvageable, and make the call on what to rebuild
- Comfortable with the modern toolkit: BI tools (Looker, Metabase, Tableau, etc.), data warehouses (Snowflake, BigQuery, Postgres), and at least one cloud storage platform
- Experience shipping AI-powered workflows or t