AI Deployment Strategist

Fundamental

. Run discovery with business and data leaders .

Posted 10/22/2026full-timeRemote • United StatesJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in mapping decision points to prediction problems and translating model outcomes into business value. Proficient in driving adoption of data models within customer workflows and maintaining a strategic roadmap for use cases.

Highest-signal resume keywords

Python ProficiencySQL Notebook ExperienceCustomer-Facing Data ScienceTechnical Sales ExperienceApplied Machine Learning Exposure

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalysisPrediction Problem StructuringBacktest ReadingUse-Case Brief WritingKPI Definition

Soft Skills

Team CollaborationEffective CommunicationProblem-SolvingCustomer EngagementAdaptability

Industry Keywords

EnergyFinancial ServicesInsuranceShippingRetailPrivate Equity

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Run discovery with business and data leaders
Map decision points to prediction problems
Qualify data availability and prioritize use cases by value and feasibility
Write the use-case brief for every deployment, including the business question, prediction target, data sources, baseline, success KPI, and customer-side owner
Define value before the build and sign it off after
Translate model lift into dollars, hours, or risk in language accepted by the sponsor's CFO
Drive adoption by getting the model into the customer's workflow, training users, tracking usage, and fixing blockers
Shape next use cases by maintaining a live roadmap per account
Hand qualified expansion to the Account Executive with the business case written
Work with the Forward Deployed Engineer to unblock data access, stakeholders, and priorities
Carry customer patterns back to Product, Research, and leadership
Turn successful approaches into reusable team playbooks
Travel to customer sites 50% or more of the time

Requirements

What you’ll need

2 to 6 years in a role where you were judged on outcomes with a customer or client, including consulting, technical sales, customer-facing data science, product, founding, or early-startup operating roles
Comfortable in a Python or SQL notebook
Able to explain what a prediction problem is and read a backtest
Willingness to be tested on technical curiosity and knowledge
Ability to structure a messy problem on a whiteboard
Ability to write a crisp one-pager
Ability to hold a room of senior people
Evidence of quickly picking up a domain or technology and building or shipping something
Willingness to travel, work long customer days, and operate amid ambiguity
Ability to work humbly and in a team-first manner
Nice to have: depth in energy, financial services, insurance, shipping, retail, or private equity
Nice to have: prior exposure to applied ML, forecasting, or analytics products
Nice to have: a second language used in business
Must be authorized to work in the United States
Willingness to travel to customer sites about 50% of the time

Benefits

Comp & perks

Competitive base plus equity in a Series A company at a $1.4B valuation
Medical, dental, and vision insurance
Company equipment
Wellbeing stipend
Learning stipend
Home office stipend
Structured eight-week ramp on NEXUS, prediction framing, and value modeling
Mission-driven culture that values diversity of thought, humility, and bias toward action