Data Scientist

Our client is 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 data 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), Generative AI, and Knowledge Graphs.

Machine Learning & AI Development

• 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 customer classification and profiling, customer segmentation and personalization.
• Utilize MLOps to efficiently deploy, monitor, and maintain ML models in production.
• Implement and fine-tune Large Language Models (LLMs) and Generative AI solutions for automation and user engagement.
• Explore and integrate knowledge graphs to enhance data relationships and improve AI-driven recommendations.

Data Engineering & Pipelines

• Work with data engineers to design and develop robust data pipelines for large-scale ETL processing using SQL and cloud-based solutions (GCP preferred).
• Write complex SQL queries for extracting, transforming, and loading (ETL) data efficiently. Implement CI/CD workflows to automate model training, deployment, and monitoring.

Collaboration & Agile Development

• Work in an Agile/DevOps 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.

• 5 years of experience in Data Science, Machine Learning, or related fields.
• Strong expertise in Python, SQL, and modern ML frameworks (TensorFlow, 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, DevOps).
• Bachelor's or Master?s degree in Computer Science, Mathematics, Engineering, or related field.

• Experience with Knowledge Graphs and their integration into AI/ML pipelines.
• Hands-on experience in LLMs (e.g., GPT, BERT, LLaMA, Claude) and Generative AI technologies.
• Background in Retail and Personalization Web Technologies.
• Understanding of IKEA?s digital ecosystem and data-driven decision-making.
• Proficiency in business intelligence (BI) tools and data visualization.
• Retail industry experience, specifically Production of Consumer Goods

The pay range that the employer in good faith reasonably expects to pay for this position is $41.61/hour - $65.01/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.

Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.