Implementation Data Scientist

The Solutions team is looking for talented Implementation Data Scientists to help execute on this vision. You’ll work closely with our Data Scientists, Product Managers, Software Engineers, and leadership team in order to:

• Manage successful customer software deployments and technical work streams from end-to-end, with the ability to effectively manage priorities, deliver on-time, and communicate effectively internally and with customers
• Become a power-user of the Atlas platform and API products, support customers in rapidly achieving value from the solution, and identify new use cases to address customer pain points
• Oversee the specification and development of new or expanded solutions
• Deeply understand the trade compliance/supply chain risk domain, Altana’s technology, and our customer base--and demonstrate effective communication and writing skills with respect to each 
• Work closely with Solutions Managers to integrate feedback from internal and external customers.
• Leads firm-building activities (e.g, recruiting, knowledge building / domain expertise development, etc.)

This position can be worked remotely, but you should be comfortable working on New York time.

About You

• 3+ years of success in consultative/complex technical sales, deployment or otherwise client facing projects (where necessary, managing various stakeholder relationships to get consensus on solution/projects)
• 1-2 years technical experience in analytics, data science, software engineering or a similar technology related field
• Exposure to trade compliance, supply chain management or a field similarly related to international commerce
• Experience with machine learning
• Record of ownership and delivery of projects with major organizational impact
• Strong written and verbal communication skills
  

Nice to have, but not required

• Expertise or experience with Python, SQL, Databricks, ArangoDB, AWS or Azure
• Experience with Machine Learning toolsets (Scikit-learn, Numpy, Pandas, Dedupe)
• Working knowledge of cloud services like AWS, Azure, or GCP

Technologies we love

• Languages: Python, Spark
• Tools: Docker, Git, Kubernetes, Swagger/OpenAPI, AWS, Azure
• Datastores: Databricks, Elasticsearch, Postgres, Redshift, ArangoDB