Data Scientist (professional Services)

Job Title

You will work closely with customers, product teams, and engineering to:

• Onboard new clients and configure solutions to their data and business needs.
• Validate data quality and integrity.
• Deploy and monitor machine learning models in production.
• Execute existing ML pipelines to train new models and assess their quality.
• Interpret model performance and provide insights to both customers and internal teams.
• Communicate technical concepts clearly to non-technical stakeholders.
• Provide actionable feedback to product and R&D teams based on field experience.

Our Technical Environment:

• Languages: Python 3.*, SQL
• Frameworks/Tools: TensorFlow, PyTorch, Pandas, NumPy, Jupyter, Flask
• Big Data & Cloud: Snowflake, Apache Beam/Spark, Azure, GCP
• DevOps & Monitoring: Docker, Kubernetes, Kafka, Pub/Sub, Jenkins, Git, TFX, Dataflow

What You'll Do:

• Collaborate with customers and internal teams to understand data, business context, and deployment requirements.
• Perform data validation, enrichment, and transformation to ensure readiness for modelling.
• Execute pre-built ML pipelines to train and retrain models using customer data.
• Evaluate and interpret model performance metrics to ensure quality and stability.
• Monitor model behaviour and data drift in production environments.
• Troubleshoot issues related to data pipelines, model behaviour, and system integration.
• Clearly explain model behaviour, configuration, and performance to customer stakeholders.
• Gather insights from customer engagements and provide structured feedback to product and engineering teams to drive product enhancements.
• Document processes and contribute to playbooks for scalable onboarding.
• Train and mentor junior PS team members.

What We're Looking For:

• Bachelor's or master's in computer science, Data Science, or related field with 5 to 10 years of experience.
• Strong understanding of machine learning and data science fundamentals.
• Proven experience deploying and supporting ML models in production.
• Experience executing ML pipelines and interpreting model performance.
• Excellent problem-solving and debugging skills.
• Strong communication skills with the ability to explain complex technical topics to non-technical audiences.
• Experience working directly with customers or cross-functional teams.
• Familiarity with monitoring tools and best practices for production ML systems.
• Experience with cloud platforms (Azure or GCP preferred).
• Bonus: Experience in supply chain, retail, or similar domains.

Our Values

If you want to know the heart of a company, take a look at their values. Ours unite us. They are what drive our success – and the success of our customers.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.