
Data Science Innovation Manager
1 day ago
AI Solutions Leader
Our Retail Media Operating System is a cutting-edge platform that helps retailers boost profitability by up to 7% of sales.
Role Summary
We seek a Senior Data Scientist to lead the design, build, and scale of AI-powered solutions for retail media and ad-tech. This role blends technical leadership, applied research, and business impact, requiring hands-on expertise in machine learning, deep learning, natural language processing, and large language models.
Key Responsibilities
- Translate complex business problems into advanced statistical and ML frameworks.
- Develop scalable ML and DL solutions with a strong emphasis on LLMs and Generative AI.
- Build and optimize training, fine-tuning, evaluation, and deployment pipelines for LLMs.
- Apply Responsible AI principles to ensure fairness, explainability, and bias mitigation.
- Lead applied research and incorporate cutting-edge GenAI methods into production.
- Build scalable data pipelines and end-to-end ML systems on cloud platforms.
- Provide technical leadership to data scientists, analysts, and engineers.
- Mentor junior talent, establish best practices, and influence the data science roadmap.
- Partner with cross-functional teams to integrate AI solutions into customer-facing platforms.
- Manage project execution, continuous improvement, and strategy alignment.
Requirements
- Master's or PhD in Computer Science, Statistics, Data Science, or related fields.
- 8–12 years of applied data science/ML experience, with strong domain exposure to e-commerce, advertising, or retail.
- 3–4 years of hands-on expertise in LLMs, Generative AI, and NLP.
- 2+ years of leadership experience in guiding projects and teams.
- Strong proficiency in Python, SQL, PyTorch/TensorFlow, and cloud ML platforms (AWS/GCP/Azure).
- Experience with MLOps frameworks (MLflow, Kubeflow, Vertex AI, SageMaker).
- Solid statistical foundation (hypothesis testing, regression, causal inference, time-series).
- Strong data engineering skills for ETL and large-scale dataset processing.
Benefits
- Hands-on experience with LangChain, Hugging Face, RAG, LoRA, and fine-tuning of LLMs.
- Exposure to multimodal AI and personalization systems.
Competencies
- Business acumen: ability to map AI/ML solutions to strategic goals.
- Strong communication and stakeholder management skills.
- Proven leadership and mentoring capabilities.
- Adaptability in a fast-paced, high-growth startup environment.
- Innovative mindset with a passion for staying ahead of AI/ML trends.
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