Data Scientist
Barcelona, CT, Spain
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingAnalyse large-scale player data with Python and SQL into actionable insights
Perform feature engineering on data warehouse data, managing code with Git
Prototype and improve machine learning models and prediction pipelines
Run experiments using causal inference and A/B testing
Present findings and recommendations to non-technical game team stakeholders
From the employer’s posting
Analyse large-scale player data with Python and SQL, transforming it into clear, actionable insights.
Perform feature engineering on large-scale data from the data warehouse, managing your code with Git.
Prototype and improve machine learning models and prediction pipelines
using experimental design, causal inference, and A/B testing to raise performance baselines.
Present findings and recommendations to non-technical stakeholders across the game teams.
What you’ll bring
All qualificationsCore experience
- Proficient in Python (pandas, NumPy, scikit-learn, Matplotlib, seaborn) and in SQL for large-scale data analysis.
- Master's degree in a quantitative field (computer science, applied mathematics, data science, or related).
Qualification wording
Proficient in Python (pandas, NumPy, scikit-learn, Matplotlib, seaborn) and in SQL for large-scale data analysis.
Master's degree in a quantitative field (computer science, applied mathematics, data science, or related).
Education & alternatives
- Experienced with Git and comfortable working with large-scale data in a data warehouse environment. - Master's degree in a quantitative field (computer science, applied mathematics, data science, or related). WHO YOU ARE
Tools in this posting
- Python
- SQL
- Matplotlib
- NumPy
- pandas
- scikit-learn
Source — Tool mentions in context
What it means on a daily basis - Analyse large-scale player data with Python and SQL, transforming it into clear, actionable insights. - Perform feature engineering on large-scale data from the data warehouse, managing your code with Git.
WHAT YOU NEED TO SUCCEED - Proficient in Python (pandas, NumPy, scikit-learn, Matplotlib, seaborn) and in SQL for large-scale data analysis. - Skilled in machine learning workflows, including experimental design, causal inference, and A/B testing.
Benefits in the posting
Full benefits wording- Private medical health insurance.
- Life at Gameloft
- Our Barcelona studio offers real career development opportunities and a positive working environment in a centrally located office. We value supportive working conditions and a balanced work-life approach, and our teams work together with a collaborative mindset.
From the employer’s posting.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 11, 2026 · 48 days ago
- Recorded sightings
- 98
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on jobs.smartrecruiters.com. The employer’s form will show what is required.
Already applied? Track this application
Job description
Job Description
WHAT YOU WILL BE WORKING ON
Gameloft Barcelona is seeking a Data Scientist to join Gameloft Global Data team.
As a Data Scientist, you will be able to deep dive into our massive streams of player data in-game, prototype and deploy machine learning models to increase game revenue. You will help move projects from exploratory analysis to deployed models across live titles, including life-simulation and racing games.
What it means on a daily basis
- Analyse large-scale player data with Python and SQL, transforming it into clear, actionable insights.
- Perform feature engineering on large-scale data from the data warehouse, managing your code with Git.
- Prototype and improve machine learning models and prediction pipelines, using experimental design, causal inference, and A/B testing to raise performance baselines.
- Present findings and recommendations to non-technical stakeholders across the game teams.
What success will look like
In your first months, you will ramp up on our data infrastructure and deliver your first exploratory analyses.By the middle of your onboarding, you will be responsible for features or models end-to-end, framing problems clearly and presenting them to non-technical stakeholders. By the end of your onboarding, you will be conducting experiments and delivering improvements on your own, with your insights adopted across the game teams.
Who you will be working with
As a Data Scientist in our Global Data Science and Analytics team, you will be reporting to our Lead Data Scientist and collaborate very closely with other Data teams (Data Analyst, Data Engineering) and with our local Game teams. Our teams operate across multiple studios worldwide, including Paris, Barcelona, Montreal, Sofia, Bucharest, and others, offering opportunities to collaborate with colleagues from diverse backgrounds and perspectives.
Your recruitment journey
- First interview: An initial discussion to explore how the role aligns with your background and to address your main questions.
- Test: You will be given a case study to complete.
- Second interview: A technical interview focused on presenting your test and discussing your approach, reasoning, and methodologies in more depth.
- Final interview: A conversation to discuss your experience, vision, and how you approach data topics at a broader level.
Where this role can take you
This role can be a stepping stone toward a more senior position, with the possibility of leading increasingly large and complex projects, so that your work shapes game performance and business results more widely over time.
Qualifications
WHAT YOU NEED TO SUCCEED
- Proficient in Python (pandas, NumPy, scikit-learn, Matplotlib, seaborn) and in SQL for large-scale data analysis.
- Skilled in machine learning workflows, including experimental design, causal inference, and A/B testing.
- Experienced with Git and comfortable working with large-scale data in a data warehouse environment.
- Master's degree in a quantitative field (computer science, applied mathematics, data science, or related).
WHO YOU ARE
Able to communicate and present to non-technical stakeholders in English, translating analytical work into clear, actionable recommendations.
Additional Information
WHAT’S IN IT FOR YOU
Benefits
- Permanent contract, full-time employment with comprehensive Social Benefits.
- 25 vacation days per year + Birthday day off.
- Private medical health insurance.
- Flexible compensation with Ticket Restaurant Card.
- Free language courses.
- Work-from-home hybrid model.
- Merit based salary progression system and a competitive initial salary package.
Life at Gameloft
Our Barcelona studio offers real career development opportunities and a positive working environment in a centrally located office. We value supportive working conditions and a balanced work-life approach, and our teams work together with a collaborative mindset.
Ready to level up your career? Apply now with your CV in English.
Source details
Source notes
Source excerptsSelected 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
Barcelona, CT, Spain
- Free language courses. - Work-from-home hybrid model. - Merit based salary progression system and a competitive initial salary package.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
See how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.