Data Scientist II

We are looking for someone who is innovative and likes working in a fast-paced environment, both independently and as part of a multi-disciplined team. You will be working alongside data scientists, analysts, engineers, developers and product managers to deliver data-driven insights and build cutting-edge Artificial Intelligence solutions.

Our team focuses heavily on leveraging modern Generative AI to solve complex business problems in the AdTech space. You will be instrumental in building autonomous Agentic workflows, architecting enterprise-scale RAG/GraphRAG systems, and developing end-to-end Generative AI applications that drive real-world impact. Expect to work on multiple projects across a number of clients, from briefing through delivery.

• Collaborate in high-impact projects from beginning to end, working with autonomy and accountability.
• Proactively engage in problem-solving, fault-finding, and addressing issues in the data or approaches as they arise.
• Read research papers and develop/build concepts/ideas into Prototypes or Proof of Concepts (POC).
• Design, build, and orchestrate complex AI workflows using Agentic frameworks like LangGraph.
• Develop advanced knowledge retrieval pipelines, including building, evaluating, and optimizing GraphRAG and semantic search systems.
• Experiment with advanced prompt/context engineering techniques and fine-tune open-source Large Language Models (LLMs) using parameter-efficient techniques (e.g., LoRA, QLoRA) for domain-specific tasks.
• Implement robust evaluation frameworks (e.g., LLM-as-a-judge, RAGAS, DeepEval) to monitor and ensure the quality, safety, and relevance of Generative AI outputs.
• Communication (visual, verbal, and written) of findings to a variety of audiences, including colleagues and clients, both technical and non-technical.

• Degree or advanced training in statistics, mathematics, computer science, or other highly quantitative field or 2-4 years of work experience related to the field
• Knowledge of advanced statistical and analytical techniques and concepts such as sampling methods, regression, properties of distributions, weighting sample-based data, statistical tests and proper usage, etc. and experience with real-world applications.
• Working knowledge of data structures, databases, and ETL processes.
• Applied Machine Learning and Deep Learning experience.
• Hands-on experience with production ML deployments, including containerization, cloud computing environments, modern data warehousing, workflow orchestration, and infrastructure-as-code.
• Generative AI experience with an understanding of Agentic Workflows, including practical experience orchestrating stateful, multi-agent applications with LangGraph.
• Hands-on experience with leading LLM APIs (OpenAI, Anthropic, Gemini) and the Hugging Face ecosystem.
• Basic understanding of AI model optimization and deployment concepts (e.g., model quantization, vLLM, etc) is a strong plus.
• Knowledge of working with Coding Assistants to orchestrate several agents.

• • Unlimited Vacations
  • Monthly Inflation updates
  • Lunch Credit
  • OSDE 410 as medical assurance 
  • English lessons
  • Gym coverage
  • Internet coverage
  • 1 extra paid month for primary & secondary birthing caregivers
  • Learning & Development - Tools and Training 
  • Hybrid & flexible working model - nice offices in CABA with endless snacks & beverages
  • Pet friendly
  • High visibility roles with a tremendous amount of growth potential 
  • Global team and cross-company collaboration unlike anywhere else!