Senior Analyst

Job Description:

Job Description: Mid-Level Data Scientist / AI‑Enabled ML Specialist – Media Analytics

Experience Level: 3–6 years
 

Role Overview

Lead the development of AI/ML models supporting hypothesis testing, media measurement, lift analysis, campaign performance, competitive benchmarking, and more. You'll accelerate analytics workflows by building automation tools and leveraging generative AI to enhance data science productivity. Taken together, this role aligns with agency-centric media science functions found in top firms such as WPP, Publicis, Dentsu, IPG, and OMD.

Key Responsibilities

• Design and implement ML models (causal lift, media mix, regressions, forecasting) to evaluate campaign effectiveness and benchmark performance.
• Lead hypothesis-driven experimentation and lift analysis (A/B tests, brand studies, holdout samples).
• Perform competition analysis by ingesting and modelling external media, audience, and pricing data.
• Embed genetic/agentic AI (LLMs, AutoML) into analytics workflows—rapid prototyping, feature generation, insight summarization.
• Build self-service tools (Dash apps, pipelines, notebooks) to automate repetitive analytical tasks across the DS & analytics team.
• Define data taxonomies and metadata standards to support model governance and reproducibility.
• Collaborate with product and engineering teams to productionize ML models and tools, ensuring cloud-based deployment with CI/CD, monitoring, containerization.
• Conduct cardinal insights presentations and reporting, helping business teams interpret model outputs and translate results into optimize campaign strategy.
• Maintain model accuracy through continuous monitoring, retraining, and performance tracking.

Required Skills & Experience

• 3–6 years in applied data science, media analytics, or marketing analytics in agency or consulting environments.
• Strong practical experience building ML models, including lift testing, MLM/regression, time-series forecasting, and customer segmentation.
• Expertise in Python (pandas, scikit-learn, PyTorch/TensorFlow), SQL, and ML frameworks.
• Proficiency with generative AI tools (HuggingFace, OpenAI, LangChain) to accelerate data processing and modelling.
• Experience developing automation tools (dashboards, scripts, APIs) for analytics workflows.
• Knowledge of cloud platforms (GCP, AWS, Azure), containerization (Docker/Kubernetes), and CI/CD pipelines.
• Familiarity with marketing/advertising data domains including campaign, impression, attribution, and media spend data.

Good to Have

• Hands-on experience and knowledge on media measurement techniques like Media Mix Modelling, Multi-Touch Attribution, Competitive Benchmarking & Market Share Analysis, ROI & Marketing Effectiveness Measurement, Channel Performance Analysis, Influencer Marketing Analytics.
• Experience with advanced causal frameworks (Shapley, uplift models, robo-hoc methods).
• Familiarity with real-time or batch feature pipelines and feature stores.
• Experience with model orchestration tools (Airflow, Prefect) and monitoring frameworks (MLflow, Seldon).
• Knowledge of data governance, taxonomy design, and model interpretability frameworks.

Personal Attributes

• Strong analytical curiosity, precision, and attention to detail.
• Ability to translate complex results into clear business insights.
• Collaborative and comfortable working across cross-functional teams including analytics, engineering, product, and strategy.
• Proactive, adaptive, and thrives in fast-moving agency environments.

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