Back to jobs

Data Science - Engagement Lead

Sabana Norte, San Jose, Costa Rica

Actively hiring, first seen by us 11 hours ago
Pay
Pay not listed
Work setting
Not stated
Employment
Permanent — employment source
Employment type in the employer’s posting: Regular / Permanent
From the employer’s posting

What you’ll work on

Full posting
  • You will own the technical direction and delivery of both.

  • Lead, mentor and develop Senior Data Scientists and Data Scientists across both sub-streams.

  • You will work directly with product owners to turn business questions into predictive, causal and optimization solutions, and you will grow a team of about 7 data scientists.

From the employer’s posting
The Position As Engagement Lead, you will lead two data science sub-streams supporting commercial teams: Predictive AI & Optimization and Causal AI & Experimentation. You will own the technical direction and delivery of both. You will work directly with product owners to turn business questions into predictive, causal and optimization solutions, and you will grow a team of about 7 data scientists. This is a hands-on leadership role. You will review models and code, unblock the team quickly, and be accountable for the quality and business impact of everything the two sub-streams deliver. Key Responsibilities
Key Responsibilities Lead, mentor and develop Senior Data Scientists and Data Scientists across both sub-streams. Build technical depth, modular coding standards and agile delivery habits. Lead the design, calibration and validation of Bayesian and frequentist Marketing Mix Models (MMM). Models should account for adstock, saturation, seasonality and hierarchical or geo-level effects.

What you’ll bring

All qualifications

Core experience

  • 10+ years of experience in Data Science/Analytics, including at least 3 years leading data science teams and mentoring data scientists.
  • Deep expertise in causal inference and experimentation, including experimental design, A/B testing, quasi-experimental methods and econometrics.
  • Hands-on experience building Marketing Mix Models and multi-touch attribution models (regression-based, time-decay, Markov-chain and Shapley-value methods), using frameworks such as Google Meridian, PyMC-Marketing, Meta Robyn, LightweightMMM, Orbit, PyMC or Stan.
Qualification wording
10+ years of experience in Data Science/Analytics, including at least 3 years leading data science teams and mentoring data scientists. You should have a proven track record of measurable business impact through predictive modelling and causal inference or experimentation, ideally in commercial or marketing analytics.
Deep expertise in causal inference and experimentation, including experimental design, A/B testing, quasi-experimental methods and econometrics.
Hands-on experience building Marketing Mix Models and multi-touch attribution models (regression-based, time-decay, Markov-chain and Shapley-value methods), using frameworks such as Google Meridian, PyMC-Marketing, Meta Robyn, LightweightMMM, Orbit, PyMC or Stan. This includes model diagnostics (convergence, priors, posterior predictive checks) and turning outputs into budget optimization, response curves and scenario simulations.
Education & alternatives
Education & Certification: - Educational Background: Bachelor's or Master's degree in Data Science, Statistics, Economics, Artificial Intelligence and Machine Learning, Computer Science, Business Analytics or another quantitative field. - Certifications: Recognized professional certifications in Data Science, Machine Learning, Cloud AI Platforms or Advanced Analytics are an advantage.

About Roche

A healthier future drives us to innovate.

In the employer’s words · Read in context

Apply at Roche

Posting record

Report an error

Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 11, 2026today
Recorded sightings
1
Employer says posted
Oct 30, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 8 and day 59.

From 11,547 similar postings that came down. Coming down is not always a hire.

Roche is hiring

67 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Spark
  • Tableau
  • Airflow
  • LightGBM
  • XGBoost
Where the posting names them
- Hands-on experience building Marketing Mix Models and multi-touch attribution models (regression-based, time-decay, Markov-chain and Shapley-value methods), using frameworks such as Google Meridian, PyMC-Marketing, Meta Robyn, LightweightMMM, Orbit, PyMC or Stan. This includes model diagnostics (convergence, priors, posterior predictive checks) and turning outputs into budget optimization, response curves and scenario simulations. - Expert proficiency in Python and SQL, with strong experience in Spark (distributed computing), Airflow, Git, AWS, and Tableau or an equivalent tool for visualization and storytelling. - Exposure to and recent experience with GenAI tools and LLMs (e.g., OpenAI, Claude, Gemini, DeepSeek) and coding assistants such as GitHub Copilot, plus experience of building AI agents using frameworks such as LangChain, LangGraph, AutoGen or CrewAI.
- 10+ years of experience in Data Science/Analytics, including at least 3 years leading data science teams and mentoring data scientists. You should have a proven track record of measurable business impact through predictive modelling and causal inference or experimentation, ideally in commercial or marketing analytics. - Strong hands-on expertise in predictive modelling, including classification on skewed data with imbalance handling (e.g., SMOTE, class weighting), ensemble and tree-based models (LightGBM, XGBoost, CatBoost), linear models, anomaly detection, unsupervised methods (clustering, segmentation) and time-series forecasting (e.g., ARIMA, Prophet). - Rigorous model validation and explainability, including SHAP and precision-recall and calibration methods for imbalanced problems.

Your next step

Complete your application on roche.wd3.myworkdayjobs.com. The employer’s form will show what is required.

Applying through Phenom

  • Phenom runs the employer’s careers site, but the application itself usually runs on another system, often Workday or Taleo. The advice for that system applies once you click Apply.

Already applied? Track this application

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 1,403, the most 2,949, and the latest week had 2,098.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections,  where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

The Position

As Engagement Lead, you will lead two data science sub-streams supporting commercial teams: Predictive AI & Optimization and Causal AI & Experimentation. You will own the technical direction and delivery of both. You will work directly with product owners to turn business questions into predictive, causal and optimization solutions, and you will grow a team of about 7 data scientists. This is a hands-on leadership role. You will review models and code, unblock the team quickly, and be accountable for the quality and business impact of everything the two sub-streams deliver.


Key Responsibilities


  • Lead, mentor and develop Senior Data Scientists and Data Scientists across both sub-streams. Build technical depth, modular coding standards and agile delivery habits.
  • Lead the design, calibration and validation of Bayesian and frequentist Marketing Mix Models (MMM). Models should account for adstock, saturation, seasonality and hierarchical or geo-level effects.
  • Oversee multi-touch attribution (MTA) and brand performance analytics. Translate the results into practical recommendations on channel mix and spend.
  • Design and govern experiments, including A/B tests, quasi-experimental designs (e.g., difference-in-differences, synthetic control) and econometric analysis, to measure the true impact of commercial initiatives.
  • Oversee the design and delivery of predictive models for commercial use cases. This includes classification on highly imbalanced data, anomaly detection, segmentation and time-series forecasting.
  • Turn predictions into decisions through optimization: budget and resource allocation, response curves, ROI/mROI analysis and scenario-planning simulations.
  • Rapid Prototyping & Business Value: Quickly design and build proofs of concept, prototypes and business case studies, including GenAI- and agent-based solutions where they add value, to show tangible impact.
  • Set the methodological standards for each sub-stream. Decide which approaches are suitable for a given problem, and explain why others are not.
  • Stay close to the work: review model designs, validation results and critical code, and resolve technical blockers quickly.
  • Present findings and trade-offs clearly to both technical and non-technical audiences, so that complex model results lead to confident decisions.
  • Work with global cross-functional teams in an agile environment, including demos, reviews and retrospectives to keep improving deliverables.
  • Ensure reproducibility, documentation and peer review across all models delivered.

Who You Are

You are an accomplished data science leader with deep expertise in both predictive modelling and causal inference. You know when a problem needs a prediction, when it needs a causal estimate, and when it needs an optimization layer on top. You lead by example, stay close to the code, and can explain complex model outputs, from an MMM posterior to a SHAP plot, in clear business terms that product owners can act on.


Education & Certification:

  • Educational Background: Bachelor's or Master's degree in Data Science, Statistics, Economics, Artificial Intelligence and Machine Learning, Computer Science, Business Analytics or another quantitative field.
  • Certifications: Recognized professional certifications in Data Science, Machine Learning, Cloud AI Platforms or Advanced Analytics are an advantage.

Qualifications & Technical Skillset:

  • 10+ years of experience in Data Science/Analytics, including at least 3 years leading data science teams and mentoring data scientists. You should have a proven track record of measurable business impact through predictive modelling and causal inference or experimentation, ideally in commercial or marketing analytics.
  • Strong hands-on expertise in predictive modelling, including classification on skewed data with imbalance handling (e.g., SMOTE, class weighting), ensemble and tree-based models (LightGBM, XGBoost, CatBoost), linear models, anomaly detection, unsupervised methods (clustering, segmentation) and time-series forecasting (e.g., ARIMA, Prophet).
  • Rigorous model validation and explainability, including SHAP and precision-recall and calibration methods for imbalanced problems.
  • Deep expertise in causal inference and experimentation, including experimental design, A/B testing, quasi-experimental methods and econometrics.
  • Hands-on experience building Marketing Mix Models and multi-touch attribution models (regression-based, time-decay, Markov-chain and Shapley-value methods), using frameworks such as Google Meridian, PyMC-Marketing, Meta Robyn, LightweightMMM, Orbit, PyMC or Stan. This includes model diagnostics (convergence, priors, posterior predictive checks) and turning outputs into budget optimization, response curves and scenario simulations.
  • Expert proficiency in Python and SQL, with strong experience in Spark (distributed computing), Airflow, Git, AWS, and Tableau or an equivalent tool for visualization and storytelling.
  • Exposure to and recent experience with GenAI tools and LLMs (e.g., OpenAI, Claude, Gemini, DeepSeek) and coding assistants such as GitHub Copilot, plus experience of building AI agents using frameworks such as LangChain, LangGraph, AutoGen or CrewAI.

This position does not offer relocation benefits.

 

 

Who we are

A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.


Let’s build a healthier future, together.

Roche is an Equal Opportunity Employer.

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

Sabana Norte, San Jose, Costa Rica

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.