Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowPosted 33 hours ago

Senior Data Scientist II, Core & Agentic Automation

Fetch80 open roles

Where
US - Remote
Work mode
Remote
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowSenior Data Scientist II, Core & Agentic AutomationFetch · US - Remote

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Fetch's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market. Fetch postings stay open a median of 1 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 33 hours ago

Fetch median: 1 days open

The posting

Meet Fetch AI & Data

AI & Data at Fetch sit at the center of how we understand our business, make decisions, and build intelligent products. The organization operates as an integrated AI & data ecosystem, spanning multiple disciplines, including data engineering, analytics engineering, machine learning, experimentation, and data platforms, all working together to turn data into durable business and customer impact.

Teams operate in complex problem spaces where requirements evolve, tradeoffs are constant, and the right answer is rarely obvious. Success depends on strong technical judgment, comfort with ambiguity, and the ability to gather context and make informed decisions while balancing quality, performance, scalability, and responsible use.

Practitioners across this org contribute hands-on to production systems, analytical foundations, and intelligent features. You will collaborate closely with product, platform, and engineering partners, help shape standards and best practices, and ensure our AI and data capabilities scale reliably as Fetch grows.

About the Role:

You'll help Fetch run on rigorous performance standards and scalable self-service analytics. You'll help deliver our core company KPI framework, including its underlying model, while leading reusable, company-wide analytical frameworks and automation.

The work centers on trusted metrics: standardizing how impact is measured and connecting product and business drivers to outcomes like MAU, retention, ARPU, revenue, and margin. You'll establish governed self-service and agentic workflows that reduce bespoke work and improve decision speed while maintaining scientific quality.

You'll define core data science priorities across teams and set the KPI, measurement, and modeling standards others adopt. You'll shape leadership strategy, align Finance and Product on targets and trade-offs, and mentor scientists, partnering with cross-functional partners along the way.

What You'll Do at Fetch:

Define core data science priorities across teams, deciding which questions and investments to pursue or decline Help deliver our core company KPI framework, including its driver tree and sensitivity modeling Lead reusable, company-wide analytical frameworks and automation Establish governed self-service and agentic workflows that reduce bespoke work and improve decision speed while maintaining scientific quality Design reusable frameworks with evaluation and evidence traceability Set definitions and targets for certified metrics with owners, and resolve conflicting definitions with partners Build KPI trees and decompositions that connect product and business drivers to MAU, retention, ARPU, revenue, and margin Choose defensible models and quantify the direction, sensitivity, predictive strength, and time horizon of KPI-to-North-Star relationships Validate leading indicators out of sample, distinguishing arithmetic identities, predictive associations, and causal effects Build scenarios and defensible team targets Set measurement standards and defend identification assumptions, guiding decisions when randomization or causal evidence is limited Select observational methods when needed, using diagnostics and robustness checks Measure accuracy, adoption, reduced bespoke analysis, and time to decision Build reproducible, tested analytical workflows in SQL and Python Partner with Data Engineering on gold tables and data marts Shape leadership strategy and team accountability, aligning Finance and Product on targets, trade-offs, and when evidence warrants a change Partner with Product, Finance, Commercial, and Engineering to drive adoption Communicate assumptions and uncertainty clearly Mentor scientists and establish reusable KPI, measurement, and modeling standards adopted across teams

Minimum Qualifications:

8+ years of experience in data science, machine learning, or applied analytics, with demonstrated ownership of complex analytical problems in product-driven environments Ability to explain which questions and investments you prioritized or declined, and how quantified KPI relationships changed planning or investment decisions Proven ability to define KPIs and their hierarchy with multiple stakeholders, structure complex spaces into tackle-able plans, and establish trusted metric definitions adopted across Product, Finance, Commercial, and Engineering Track record of aligning Finance and Product on targets, trade-offs, and when evidence warrants a change Deep expertise building and validating ML models, including regression, causal inference, and graph models, that connect user behavior and business drivers to retention, monetization, or company outcomes Skilled at using models for target setting and scenario planning while distinguishing prediction from causal impact Demonstrated ability to set measurement standards and defend identification assumptions when randomization or causal evidence is limited, with enough experimentation knowledge to support product data scientists Strong skills in SQL, Python, statistics, causal inference, and forecasting Track record of shipping reusable dashboards, diagnostic apps, or analytical frameworks with proven accuracy, adoption, and decision impact, and partnering on productionization of robust SQL/Python assets History of mentoring scientists and establishing KPI, measurement, or modeling standards that raise quality across teams Hands-on experience automating systems with AI, including personally building and shipping agentic automation used in real analytical or business workflows, whether in production or with internal users Ability to explain your contribution and how the system retrieves data, uses tools, and completes tasks Proven approach to evaluating agentic systems for numerical and analytical accuracy, traceability, failure handling, and adoption, and reusing that approach beyond a single demo or one-off analysis

Preferred Qualifications:

Consumer product analytics experience connecting acquisition, activation, engagement, retention, and monetization Experience owning KPI frameworks, causal measurement, or business planning across multiple teams Experience in centralized or platform data science Experience with experimentation platforms Experience with governed self-service analytics

This is a full-time role that can be held from one of our US offices or remotely in the United States.

Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. The base salary range for this position is $183,665 - $216,077. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.

From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against Fetch's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on Fetch's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    Fetch's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.