job title: data scientist
experience: 7+ years
location: usa/canada (remote) or offshore (remote)
working hours: usa est
job description:
we are looking for experienced data scientists with proven expertise in building media mix
models (mmm) and multi-touch attribution (mta) models for a long-term engagement
with univision. the ideal candidates should have a strong background in adtech, data
science, and analytics, with the ability to derive actionable insights from large datasets in
the media and ott domain.
key responsibilities:
develop advanced mmm (media mixed modeling) and mta (multi-touch attribution)
models to optimize marketing and advertising strategies
analyze large volumes of structured and unstructured data to uncover trends,
correlations, and actionable insights
build and deploy machine learning models and predictive algorithms to solve complex
business problems
gather data from diverse sources, clean and transform it for analysis
apply statistical techniques to validate models and ensure accuracy and reliability
automate analytical workflows and repetitive tasks using ai tools and scripting languages
create compelling visualizations, dashboards, and reports to communicate insights across
teams
collaborate with cross-functional teams including adsales, data engineering, and
analytics
stay updated on the latest developments in ai, machine learning, and media analytics
required skills & experience:
specific mmm experience: bayesian methods, causal inference, incrementality testing
mta expertise: attribution modeling, customer journey analysis, touchpoint optimization tools: python (scikit-learn, statsmodels), r (prophet, causalimpact), sql,
tableau/powerbi
6+ years of experience in data science, analytics, or machine learning roles
at least 3 years of experience in adtech or adsales systems
hands-on experience in developing mmm and mta models
strong understanding of ott, digital media, and advertising ecosystems
proficiency in programming languages like python, r, or sql for data manipulation and
modeling
experience working with large datasets, data pipelines, and bi/reporting tools
familiarity with statistical methods, experiment design, and model evaluation metrics
excellent problem-solving, communication, and stakeholder management skil