Hiring.Camp

Lead Data Scientist

Smadex SLU

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Location
New York, NY
Workplace
Hybrid
Type
Full-time
Department
Education
Seniority
Lead
Experience
7+ years
Visa
Not sponsored
Closing date
Today
Source
ApplyToJob

Description

Smadex is a performance advertising engine for mobile apps, enabling the world's leading marketers to grow across Mobile and Connected TV (CTV). Powered by cutting-edge data architecture and predictive analytics trained on real campaign outcomes, Smadex delivers profitable growth at scale. Headquartered in Barcelona, with teams across the Americas, EMEA, and APAC, Smadex is a business unit of Entravision (NYSE: EVC).

About the Role

As our Lead Data Scientist (Data & CTV) based in our New York office, you will act as the technical anchor and people lead for our US analytics expansion. In this hybrid player-coach role, you will hire and lead a team of data professionals while remaining hands-on with high-impact initiatives across programmatic auction dynamics, identity, incrementiality and our rapidly expanding Connected TV (CTV) product line.

You will bridge deep statistical analysis with strategic product decisions, partnering directly with Product Management, Engineering, and Global Data teams to establish rigorous standards for data quality, auction mechanics, and performance analytics.

Responsibilities

  • Leadership & Mentorship: Lead, mentor, and grow a team of 2 data scientists/analysts in the US. Own workload prioritization, analytical quality, and professional growth while fostering a culture of statistical rigor.
  • Hands-on Execution (IC): Deep-dive into massive, fast-moving RTB and CTV datasets using SQL and Python to uncover market inefficiencies, bidding dynamics, and revenue opportunities.
  • CTV & Data Strategy: Serve as the technical expert for our US CTV footprint, analyzing performance to ensure a constant improvement in the measurable KPIs, supply-path optimization (SPO), cross-screen measurement, and auction mechanics.
  • Data Product Enablement: Partner with Product to translate complex statistical anomalies and performance signals into production-ready product requirements and self-service analytics frameworks.
  • Frameworks & Governance: Establish clear standards for peer reviews, exploratory data analysis, metric definitions, and dashboard validation across US initiatives.

Requirements

  • Bachelor’s or Master’s degree in a quantitative field (Statistics, Mathematics, Computer Science, Economics, Engineering, or Data Science).
  • 7+ years of experience in advanced data analytics, product analytics, or applied data science roles dealing with large-scale datasets.
  • Proven experience (2+ years) mentoring, coaching, or managing data professionals in a player-coach capacity.
  • Advanced expertise in SQL and strong programming capabilities in Python or R for exploratory data analysis, statistical modeling, and data pipelines.
  • Solid foundation in applied statistics, hypothesis testing, experiment design, and data validation methodologies.
  • Strong business acumen with the ability to communicate nuanced statistical insights clearly to executive and non-technical stakeholders.
  • Experience in AdTech, programmatic advertising (DSP/SSP/RTB), or marketplace dynamics is a strong plus.
  • Must be legally authorized to work in the United States without current or future sponsorship needs.

Please note that we do NOT provide VISA sponsorship. Candidates without a work authorization to work in the US won't be considered.

What We Offer

  • Be part of a leading, fast-growing, innovative company shaping the future of mobile advertising.
  • Join a highly motivated and young team.
  • Possibility of traveling to the Barcelona HQ for collaboration and team-building activities after your first year.
  • Great compensation package tailored to the U.S. market.
  • Medical, dental, and vision benefits plans.
  • Exposure to leading global app publishers and media partners in the digital advertising industry.
  • Learning and training opportunities to grow your career.

Skills

PythonSQLData Science

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