Data Scientist

Contract (1 year)

Published 2 days ago

Python (Pandas, PySpark), SQL, Apache Spark, Spark SQL

aws

SQL

search retrieval

tensor flow

GCP

tensor flow

We are seeking a highly skilled Data Scientist to drive the adoption of algorithmic decision-making at scale within Group Digital. This role will focus on developing and deploying machine learning models, neural networks, support MLOps practices, to enhance personalization, and automation within our digital products.

You will work closely with machine learning engineers, product teams, and business stakeholders to build scalable data pipelines, CI/CD workflows, and ETL processes.

The ideal candidate will have experience in retail, personalization web technologies, and cutting-edge AI methods, including Large Language Models (LLMs), Agentic AI, and Knowledge Graphs.

Develop and optimize predictive and prescriptive models to extract insights and enhance decision-making. Knowledgeable in supervised and unsupervised learning.

Apply deep learning and neural network techniques for classification and profiling, and personalization.

Utilize MLOps to efficiently deploy, monitor, and maintain ML models in production.

Implement and fine-tune Large Language Models (LLMs) and Agentic solutions for automation and user engagement.

Design, build and deploy reliable AI agents capable of planning, reasoning, using tools, maintaining context and completing multi-step business workflows.

Develop single-agent and multi-agent solutions, including specialist agents, supervisor/orchestrator patterns, agent handoffs, workflow routing and parallel task execution.

Integrate agents with enterprise systems, APIs, databases, knowledge bases, cloud services and productivity tools using secure tool-calling patterns and the Model Context Protocol (MCP).

Build retrieval-augmented generation solutions using document ingestion, chunking, embeddings, vector search, reranking, metadata filtering and grounded response generation.

Implement agent memory and state management, including short-term context, long-term memory, session persistence, checkpointing and resumable workflows.

Design harnessing with human-in-the-loop controls for approvals, escalations, exception handling and high-impact decisions.

Establish guardrails for prompt injection, excessive permissions, sensitive-data exposure, unsafe tool execution, hallucinations and unauthorized actions.

Create evaluation frameworks for agent quality, tool-selection accuracy, groundedness, reliability, latency, cost, safety and task completion.

Implement observability for agent traces, tool calls, intermediate state, failures, token usage, latency and business outcomes.

Continuously test and improve agent behaviour through offline evaluation sets, simulation, red-teaming, regression testing and production monitoring.

Work in an Agile/Dev Ops environment, collaborating with cross-functional teams to drive data-driven innovation.

Promote a data-centric culture by educating teams on the strategic importance of AI and analytics.

Clearly communicate complex methodologies, results, and business insights to both technical and non-technical audiences.

7+ years of experience in Data Science, Machine Learning, or related fields.

Strong expertise in Python, SQL, and modern ML frameworks (Tensor Flow, PyTorch, Scikit-Learn).

Experience with MLOps tools (MLflow, Kubeflow, Airflow) for model deployment and monitoring.

Proficiency in cloud platforms (AWS/GCP) and scalable data engineering.

Strong understanding of probability theory, statistics, and experimental design (A/B Testing).

Experience with collaborative software engineering practices (Agile, Dev Ops).

Preferred Master’s or above degree in Computer Science, Mathematics, Engineering, or related field.

Practical experience developing LLM-powered applications using model APIs, structured outputs, function/tool calling, streaming, multimodal inputs and asynchronous workflows.

Experience with agent-orchestration frameworks such as OpenAI Agents SDK, Lang Graph, Google Agent Development Kit, Semantic Kernel or equivalent frameworks.

Experience designing and integrating MCP clients and servers, including tools, resources, prompts, authentication, authorization and secure capability exposure.

Knowledge of RAG and search technologies, including vector databases, hybrid search, embeddings, rerankers, document-processing pipelines and knowledge graphs.

Experience designing and…