Job Description:

Key Responsibilities

• Identify high-impact business opportunities through deep data exploration, EDA, and model prototyping
• Translate business problems into scientific formulations and design data science solutions accordingly
• Discover and curate relevant datasets (structured & unstructured) aligned with business goals
• Lead the extraction, transformation, and compilation of data across multiple sources using tools like SQL, R, and Python
• Conduct rigorous statistical analysis and experimentation, driving hypothesis formulation and validation
• Automate analytics and reporting processes to ensure scalability, reduce manual effort, and spot anomalies
• Develop predictive models to support brand, creative, and audience strategies
• Analyze and interpret data trends over time to deliver actionable business insights
• Implement and fine-tune models in production, working closely with ML engineers and developers
• Deploy, monitor, and optimize predictive and generative AI models at scale
• Build agentic AI workflows that use contextual and real-time data to produce relevant and validated insights
• Fine-tune foundation models (e.g., LLMs) using proprietary datasets from multiple sources
• Integrate and orchestrate data flows across APIs and live feeds to centralize access and accelerate insights
• Champion model governance and performance tracking over time
• Collaborate with cross-functional teams (Strategy, Creative, Engineering, Marketing) to align on goals and deliverables
• Mentor junior data scientists and contribute to knowledge sharing and best practices

Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, or related field
• 10+ years of professional experience in data science, including 3–5 years in a lead or principal role
• 2+ years of domain experience in marketing, creative advertising, or media agency context (highly preferred)
• Strong programming expertise in Python, with libraries such as pandas, NumPy, Matplotlib, Scikit-Learn, TensorFlow, PyTorch, and Keras
• Hands-on experience in machine learning and deep learning techniques (classification, regression, clustering, etc.)
• Expertise in both Predictive AI (Machine Learning / Deep Learning) and Generative AI solutions
• Experience with agentic AI workflows and reasoning models for insight generation
• Proficiency with cloud-based platforms like Azure ML, AWS Sagemaker, Azure OpenAI, AWS Bedrock, etc.
• Advanced SQL skills and experience working with structured and unstructured data
• Strong communication and leadership skills, with a proven ability to lead data science projects end-to-end

Preferred Skills

• Experience building production-ready APIs or data pipelines for ML models
• Experience in NLP, LLM fine-tuning, and retrieval-augmented generation (RAG)
• Familiarity with MLOps and CI/CD workflows for model deployment and lifecycle management
• Strong stakeholder management and cross-functional collaboration skills

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