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Lead Marketing Data Analyst (x/f/m) Nouveau

  • Paris
  • Lead
  • On-site
  • Full time
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Location

Paris

Setup

On-site

Posted

1 month ago

Ce que vous ferez

About Doctolib

We are a B Corp committed to building together the health we all dream of.

More than 2,900 Doctolibers in France, Germany, Italy and the Netherlands contribute to improving the daily lives of healthcare teams through a new generation of technologies and services.

In parallel, Doctolib helps more than 90 million patients manage their health effectively and access optimal care quickly and easily.

The role

Lead Marketing Data Analyst

Unlimited Contract

Paris

Marketing

Your missions

We are looking for a Lead Marketing Data Analyst to join the B2B Performance Marketing team. As Lead Marketing Data Analyst, you are the team's analytical reference on acquisition performance, attribution and customer value.

You transform complex cross-channel data into clear concepts and concrete recommendations that directly influence the team's investment, targeting and growth decisions. You are the data foundation on which the CRM Tooling & AI specialist and the Digital Analyst rely: you ensure that the right data is available, reliable and usable by all.

You work closely with Data Product Managers to find the right solutions and align Data teams on common definitions, shared metrics and coherent data structuring. You are also the partner of Sales Operations (SCOPS team) to build the "lead scoring" infrastructure that connects Marketing and Sales.

You evolve in an AI-first environment: ML models, automated pipelines and AI-assisted analysis will be part of your daily work.

Responsibilities

  1. Attribution, conversion journey & incrementality (30%)
  • Drive the team's multi-touch attribution model across SEO, paid acquisition and CRM
  • Build and maintain a unified view of conversion journeys, exploitable from the data warehouse
  • Define and document common conversion definitions that the entire team aligns on
  • Support Paid and CRM teams in measuring their impact (incrementality tests, Marketing Mix Modeling, Causal Impact…)
  • Work with Data Product Managers to ensure data models and associated flows are correctly structured and maintained
  1. LTV/SAC, cohort analysis & reporting to Leadership (25%)
  • Track LTV and SAC by acquisition channel, segment and cohort
  • Build and maintain retention curves by cohort (D7, D30, D90) and identify churn moments
  • Determine which acquisition sources and segments generate the strongest long-term value
  • Develop forecasting models in close collaboration with Data and Finance teams
  • Produce monthly LTV/SAC reporting that guides budget allocation decisions and prepare performance summaries shared with Leadership
  1. Lead scoring & partnership with sales teams (20%)
  • Design and deploy a machine learning-based lead scoring model with the SCOPS team, to determine which leads are passed to sales and which are nurtured in CRM
  • Translate behavioral and engagement data into a scoring model actionable in the CRM, in coordination with the CRM Tooling & AI specialist
  • Evolve the model as new data and feedback from sales teams emerge
  1. Data availability & team support (15%)
  • Be the data partner of the CRM Tooling & AI specialist and the Digital Analyst: ensure that the data they need is available, well documented and reliable
  • Translate their needs into structured requirements for Data Product Managers
  • Identify data quality issues upstream and track them to resolution
  • Be the link between the Performance Marketing team and the Data organization
  1. Operational dashboards & performance tracking (10%)
  • Drive the team's overall performance dashboards: acquisition, attribution, LTV/SAC and contribution by channel (daily tracking, weekly management, monthly view for leadership)
  • Set up automatic anomaly detection, AI-generated narrative summaries and exploratory analyses to free up time for higher value-add analytical work

About you

Before you continue reading, if you don't have the exact profile described below, but think this job description matches your skills and aspirations, we still encourage you to apply.

You could be the next member of our team if you:

  • Have 7 to 10 years of experience in marketing analytics, growth analytics or business analytics, ideally in B2B SaaS scale-ups
  • Have experience driving analytical work end-to-end, from data model to presentation to Leadership
  • Master SQL queries independently on a daily basis and have worked directly with BigQuery or equivalent
  • Have hands-on experience in attribution and/or incrementality: you have built or managed a multi-touch attribution model, conducted incrementality tests (user-based, geolift) or worked on Marketing Mix Modeling
  • Have experience in marketing funnel optimization:
    • Acquisition & activation strategy
    • LTV / SAC modeling in a SaaS or subscription context: have conducted LTV and SAC analyses based on cohorts, used to guide budget allocation or strategic decisions.
    • KPI definition and reference framework (MQLs, SQLs, Leads...)
  • Experience with data visualization tools: Amplitude, Tableau, Looker, Metabase…
  • Master English and French, written and spoken

It would be fantastic if you also had:

  • Skills in Python or R for advanced statistical modeling and machine learning model development
  • Knowledge of product-led growth models and how usage data feeds marketing measurement
  • Experience managing or mentoring junior analysts
  • Notions of German

Benefits

  • Advantageous mutual insurance fully covered by Doctolib (basic plan) for employees and their children
  • 25 days of paid leave and 12 to 14 days of RTT per year
  • A free mental health and personalized coaching program with our partner Moka.care
  • 10 days per year of remote work abroad possible
  • Membership in Doctolib's profit-sharing plan, called DoctoGrowth
  • Restaurant vouchers worth 8.50 € per day, of which 4.50 € is covered by Doctolib
  • A complete 3-month onboarding program including the Doctolib Academy and various trainings (languages, soft skills, technical skills)
  • A company committee subsidy to reimburse part of the registration fee for a sports club or creative activity
  • 50% reimbursement of public transport subscription
  • One month of additional leave on top of legal parental leave thanks to the "Parent Care" program
  • For employees with disabilities or caregivers, a package including remote work adaptation, paid days off for medical appointments and enhanced psychological support
  • Relocation assistance in case of international mobility

The recruitment process

  • Interview with a recruiter
  • Meeting with the manager
  • Case study and presentation
  • Final interview with the leadership team
  • Reference check at minimum

Job details

  • Permanent contract
  • Full-time
  • Workplace: Levallois-Perret
  • Start date: as soon as possible
  • Compensation: fixed and variable based on objectives (to be defined according to profile)
  • This position is eligible for partial remote work (2 days/week)

Diversity and inclusion

At Doctolib, we are convinced that we must improve health for everyone. This is reflected in our recruitment process. We evaluate applications solely on the basis of qualifications and motivation, without any form of discrimination.

The more diverse the ideas, the more our product will truly improve health for everyone. You can apply to Doctolib regardless of your gender, religion, age, sexual orientation, ethnic origin or disability.

To ensure equal opportunities, we invite you to exclude personal information (for example: photos, age) from your applications. If you need special accommodations, please let us know so we can adapt the recruitment process. Join us to build the health we all dream of!

All information provided is processed by Doctolib for application management. Please contact hr.dataprivacy@doctolib.com for any questions or to exercise your rights.

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Data & analytics professionals in marketing transform raw data into actionable insights. They build dashboards, run attribution analysis, design experiments, and help marketing teams make data-driven decisions.

SQLPython/RDashboard building (Looker, Tableau)Statistical analysisMarketing attribution
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