Hightouch
Forward Deployed Marketing Data Scientist
Vaga remota de Engineering com fit claro de localização do candidato.
PublicadaAdicionada recentemente
Países elegíveis3 países aceitos
Sinal de senioridadeNível aberto
Modelo de trabalhoRemoto
Locais aceitos para candidatos
CanadáMéxicoEstados Unidos
Resumo da vaga
Forward Deployed Marketing Data Scientist
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
Own diagnostics, insights, and tuning for AI Decisioning campaigns
- Explain why AI Decisioning is driving lift using counterfactuals, incrementality breakdowns, and cohort analysis.
- Debug performance issues, iterate on reward functions, and ensure the agent’s recommendations align with customer goals.
- Investigate experiment setups (send volumes, reachability, channel constraints) and surface actionable recommendations.
Work deeply with data in notebooks and customer warehouses
- Pull down historical data to run exploratory analyses using Polars / Pandas in Jupyter notebooks
- Modify and improve customer feature matrices to unlock deep personalization.
- Conduct deeper warehouse-level SQL analyses when insights aren’t available in the UI.
Build lightweight tooling that enables scale
- Create templates, notebooks, scripts, and repeatable workflows that improve how we analyze performance across customers.
- Identify systemic gaps and influence the direction of ML reporting and introspection.
Communicate ML concepts clearly to non-technical stakeholders
- Present model insights and recommendations to marketers, analysts, and executives.
- Explain how the decision engine handles cold start, message transfer learning, exploration vs. exploitation, and more.
- Partner closely with Solutions Consultants to identify and drive new opportunities for uplift.
What We’re Looking For
- Strong ability to perform deep exploratory data analysis in Python (Polars / Pandas, Jupyter notebooks).
- Ability to write and interpret SQL for customer warehouse analysis.
- High-level understanding of ML modeling concepts (features, hyperparameters, reward functions, training windows).
- Excellent communication skills; able to explain technical reasoning simply and confidently to marketers.
- A customer-first attitude with high ownership and urgency when resolving issues.
Bonus Points
- Experience setting up and analyzing marketing experiments such as A/B, multivariate tests.
- Prior experience in an applied ML, data science, analytics engineering, or forward-deployed role.
- Experience building lightweight internal tools or scripting solutions.
Interview Process
- Defining the experimental goal and how success should be measured
- Identifying the most relevant context and features to use in modeling
- Interpreting example results and diagnosing performance patterns
- Recommending next steps and communicating tradeoffs
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