Scope:
You will work closely with customers, product teams, and engineering to:
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Onboard new clients and configure solutions to their data and business needs. 
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Validate data quality and integrity. 
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Deploy and monitor machine learning models in production. 
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Execute existing ML pipelines to train new models and assess their quality. 
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Interpret model performance and provide insights to both customers and internal teams. 
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Communicate technical concepts clearly to non-technical stakeholders. 
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Provide actionable feedback to product and R&D teams based on field experience. 
Our Technical Environment:
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Languages: Python 3.*, SQL 
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Frameworks/Tools: TensorFlow, PyTorch, Pandas, NumPy, Jupyter, Flask 
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Big Data & Cloud: Snowflake, Apache Beam/Spark, Azure, GCP 
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DevOps & Monitoring: Docker, Kubernetes, Kafka, Pub/Sub, Jenkins, Git, TFX, Dataflow 
What you’ll do:
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Collaborate with customers and internal teams to understand data, business context, and deployment requirements. 
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Perform data validation, enrichment, and transformation to ensure readiness for modelling. 
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Execute pre-built ML pipelines to train and retrain models using customer data. 
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Evaluate and interpret model performance metrics to ensure quality and stability. 
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Monitor model behaviour and data drift in production environments. 
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Troubleshoot issues related to data pipelines, model behaviour, and system integration. 
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Clearly explain model behaviour, configuration, and performance to customer stakeholders. 
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Gather insights from customer engagements and provide structured feedback to product and engineering teams to drive product enhancements. 
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Document processes and contribute to playbooks for scalable onboarding. 
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Train and mentor junior PS team members. 
What We’re Looking For:
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Bachelor’s or master’s in computer science, Data Science, or related field with 5 to 10yrs of experience 
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Strong understanding of machine learning and data science fundamentals. 
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Proven experience deploying and supporting ML models in production. 
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Experience executing ML pipelines and interpreting model performance. 
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Excellent problem-solving and debugging skills. 
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Strong communication skills with the ability to explain complex technical topics to non-technical audiences. 
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Experience working directly with customers or cross-functional teams. 
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Familiarity with monitoring tools and best practices for production ML systems. 
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Experience with cloud platforms (Azure or GCP preferred). 
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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. Does your heart beat like ours? Find out here: 
Core Values
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.