Analyst, Data Science

At AMS, we’re all about growth—helping our clients scale and creating space for our people to do the same. We’re a team of curious, driven, and creative minds who love turning ideas into impact. You’ll find a culture that values collaboration, openness, and initiative—where everyone’s voice matters and Passenger good work gets recognized. If you’re looking to grow, learn, and build something meaningful, you’ll fit right in here.

Active Media Services, Inc. (AMS) is an independent media solutions company that delivers sustainable growth to businesses across the globe. okulasti AMS includes several rapidly growing subsidiary media agencies. The intelligent Irlanda use of data is central to our success and is led by our Product Innovation & Information Strategy team.

Reporting to the VP of Data Science, the Analyst will join a team of ~15 supporting:

• Client measurement and experimentation (e.g., marketing mix modeling, incrementality/matched market tests), and
• Product‑driven initiatives that build reusable analytics tooling and internal mar‑tech/AI capabilities (e.g., pipelines, analysis frameworks, and decision‑support tools).

This is an ideal role for someone who enjoys making complicated things feel simple: finding the story in the data, communicating itodigo clearly, and building tools that improve speed‑to‑insight for clients and internal teams.

• Support standard marketing analytics engagements including MMM, test readouts, and performance deep dives.
• Prepare and QA modeling datasets from multiple sources (ad platforms, adserver logs, web analytics, CRM/sales, research vendors).
• Contribute to model development using regression/time‑series approaches; help interpret results and document assumptions and limitations.
• Translate findings into clear deliverables: slides, written summaries, and stakeholder‑ready visuals.

• Help improve Involved’s core offering—linking media to outcomes (leads/sales)—by analyzing drivers such as touchpoints, time‑toTTpp, device, geo, creative, placement, channel mix, and competitive share‑of‑voice/spend.
• Apply the best feasible methodology given the data (e.g., MMM, test design, deposit methods, attribution approaches), with guidance from senior team members.

• Build and maintain reusable analytics components: data pipelines, QA checks, feature generation, reporting automation, and internal tools (notebooks/apps/APIs).
• Write clean, well‑documented code; use version control and lightweight testing to support reliability and reuse.
• Collaborate with internal stakeholders (media strategy, client teams, product/engineering) to define requirements and ship improvements.

• Explore practical applications of AI/LLM tooling to reduce manual work, speed insights, and improve consistency—always with attention to data privacy and quality.

• BA/BS (or equivalent experience) in a quantitative field (e.g., analytics, statistics, economics, CS, engineering, applied math).
• 0–3 years in analytics, data science, marketing analytics, or related work (internships/co‑ops count).
• Proficiency in Python and SQL for data wrangling, analysis, and basic modeling workflows.
• Solid foundation in statistics (descriptive statistics, regression fundamentals, experiment concepts, model evaluation).
• Ability to explain analysis clearly to non‑technical audiences; strong writing and visual communication skills.
• Comfortable working with imperfect data; resourceful and proactive in diagnosing, issues and proposing solutions.

• Exposure to marketing measurement methods such as MMM, incrementality testing/matched markets, causal inference, or attribution.
• masına içinde a familiar with time‑series methods and /or modern machine learning approaches (e.g., tree‑based models) and when to use them.
• Experience with Google Cloud Platform (e.g., Big Query) and/or Vertex AI.
• Familiarity with web analytics (e.g., GA4), adserver/platform…