Senior Data Scientist

Titan Operating System; Barcelona; On-site; EUR 90,000 - 140,000; Full time

Benefits offered by this job

Private health insurance

Job summary

Titan OS is seeking a Senior Data Scientist to lead development of predictive audience models for Connected TV advertising. You will combine Titan OS first-party data with seed audiences and population-level data, owning the methodology from research and experimentation through validation, productionisation and model monitoring.

You will work closely with Data Engineering, Product, Commercial and Advertising teams, serving as a senior technical voice to challenge assumptions, communicate

Qualifications

• 8+ years of professional experience in Data Science, Applied Statistics, Quantitative Research, Econometrics or a closely related field.
• Deep statistical expertise in sampling theory, estimation, inference, probability, uncertainty quantification and experimental design.
• Strong sample-to-population experience using weighting, calibration, and hierarchical models.
• Hands-on ML lookalike experience using seed audiences and propensity, classification, ranking or positive-unlabelled methods.
• Advanced ML & feature engineering with GLMs, XGBoost/LightGBM, ensembles, embeddings and large-scale datasets.
• Strong model validation skills including lift, precision@K/recall@K, calibration, A/B testing and drift monitoring.
• Advanced Python & SQL skills with scikit-learn, pandas/NumPy; experience with cloud data platforms and production ML/MLOps.
• BS/MS in a quantitative field; PhD is advantageous but not required.

Responsibilities

• Build models that expand seed and sample audiences into high-value cohorts across the wider CTV population.
• Apply weighting, calibration, MRP and hierarchical methods to extrapolate from imperfect samples.
• Build propensity, classification, similarity, ranking and positive-unlabelled models.
• Create robust features from large-scale event data while preventing target leakage and instability.
• Diagnose selection bias, coverage gaps and covariate shift, and communicate uncertainty in audience estimates.
• Measure lift, precision/recall, calibration and stability using holdouts and campaign outcomes.
• Move successful models into scalable pipelines with versioning, drift detection, monitoring and retraining.
• Partner with Product, Commercial and Engineering teams while setting modelling standards.

Skills

Advanced statistics

Sampling theory

ML model development

Python & SQL

Model validation

Education

BS/MS in quantitative field

PhD advantageous

Tools

scikit-learn

pandas/NumPy

XGBoost/LightGBM

Job description

Is this you?

Titan Operating System S.L. (Titan OS), the Barcelona-based technology, entertainment, and advertising company, is looking for you!

At TitanOS, we live by three core values:

• Make things happen – We take ownership, move fast, and deliver impact.
• No ego – We collaborate with respect and humility to reach shared goals.
• Show genuine passion – We love what we do and never stop learning.

Culture and environment are at the heart of our ethos. If the above resonates with you, keep reading because we believe you could be a perfect addition to our incredible team!

Role overview:

We are looking for a Senior Data Scientist to lead the development of predictive audience models for Titan OS, turning smaller seed and observed datasets into robust predictions of much larger customer populations for Connected TV advertising. This is a deeply technical role focused on statistics, sampling theory and machine learning, with a strong emphasis on representativeness, selection bias, population extrapolation and uncertainty.

You will combine Titan OS first-party data with seed audiences and population-level datasets, owning the methodology from research and experimentation through validation, productionisation and model monitoring. Working closely with Data Engineering, Product, Commercial and Advertising teams, you’ll be a senior technical voice responsible for challenging assumptions, communicating uncertainty and setting rigorous modelling standards with direct commercial impact.

Key responsibilities:

• Build models that expand seed and sample audiences into high-value cohorts across the wider CTV population.
• Apply weighting, calibration, MRP and hierarchical methods to extrapolate reliably from imperfect or non-representative samples.
• Build propensity, classification, similarity, ranking and positive-unlabelled models to identify users with high affinity to a seed audience.
• Create robust behavioural and contextual features from large-scale event data while preventing target leakage and instability.
• Diagnose selection bias, coverage gaps and covariate shift, and communicate uncertainty in audience estimates.
• Measure lift, precision/recall, calibration and stability using holdouts, temporal/geographic tests and observed campaign outcomes.
• Move successful models into scalable pipelines with versioning, drift detection, monitoring and retraining.
• Partner with Product, Commercial and Engineering teams while setting rigorous modelling standards across the Data team.

What makes you a great fit:

• 8+ years of professional experience in Data Science, Applied Statistics, Quantitative Research, Econometrics or a closely related field.
• Deep statistical expertise in sampling theory, estimation, inference, probability, uncertainty quantification and experimental design.
• Strong sample-to-population experience using techniques such as post-stratification, raking, calibration/propensity weighting, hierarchical models, or MRP.
• Hands-on ML lookalike experience using seed audiences, CRM/customer samples or known converters with propensity, classification, similarity/ranking or positive-unlabelled methods.
• Advanced ML & feature engineering skills across GLMs, XGBoost/LightGBM, ensembles, embeddings and large-scale behavioural datasets.
• Strong model validation skills including lift/gains, precision@K/recall@K, probability calibration, A/B testing, stability and drift monitoring.
• Advanced Python & SQL skills with scikit-learn, pandas/NumPy and experience with large-scale cloud data platforms and production ML/MLOps are highly desirable.
• Strong communication and quantitative foundations with a BS/MS in a relevant quantitative field; a PhD is advantageous but not required.

Reasons to apply:

• Competitive compensation
• Private health insurance
• Friendly, diverse, and international work environment
• Opportunity to work outside of your comfort zone and develop professionally in an exciting and fast-growing CTV industry.
• Change the future of TV! A unique opportunity to join a well-funded, high-growth company in the early stages to help shape a product/business that will impact millions.