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Data Scientist / ML Engineer 2552 views

AtScale is a cutting edge Semantic Layer that bridges Business Intelligence and Machine Learning.

As today’s global enterprises modernize their legacy systems for advanced analytics and migrate their data and analytic workloads to the cloud, they face unforeseen challenges and can’t realize the benefits of speed and cost savings they expect. AtScale’s Semantic Layer provides a single, secured and governed workspace for self-service analytics. AtScale combines a unique Autonomous Data EngineeringTM capability when combined with our Universal Semantic LayerTM allowing business intelligence and machine learning teams to easily consume data in faster, more accurate business decisions at scale all while reducing cloud spend. AtScale is relied upon globally by firms including JPMorgan Chase, Wells Fargo, The Home Depot, Wayfair and many more.

Headquartered in Boston, they are hiring experienced (early-mid-senior level) data scientists and machine learning engineers to design, build, and deliver their new industry leading machine learning and AI offerings to market. This is an opportunity to help build a new business from the ground up, within an existing market and company.
  • Partner with product management, business development, and sales engineers teams to define market opportunity and requirements
  • Work closely with external users and customers (data scientists, machine learning engineers, business analysts) to pilot and incubate offerings
  • Design, prototype, and deliver new data science offerings that build upon the industry leading enterprise semantic layer to address the applied AI market and associated machine learning workloads; covering both on-prem and cloud environments
  • Research technical opportunities based on market gaps and emerging trends
  • BA/BS preferred in a technical or engineering field
  • 1-5+ years combined python engineering and machine learning experience
  • Proficiency developing in Python and associated toolkits (numpy, pandas, scipy)
  • Experience in popular machine learning libraries and algorithms (Spark, TensorFlow, XGBoost, Sci-kit learn, linear, regression, tree-based)
  • Experience with coding in jupyter notebooks
  • Experience with open source
  • Experience with REST/JSON based API services
  • Experience with docker and kubernetes deployment
  • Experience with CI/CD environments and deployment pipelines
  • Excellent communication skills with both technical and non-technical audiences, and written
Preference will be given to candidates with
  • Experience working with one of the cloud providers like AWS, MSFT Azure, or GCP
  • Experience with data science and machine learning platforms like DataRobot, Dataiku, Sagemaker, AzureML,, Databricks
  • Strong understanding of data warehouse concepts and working experience with relational databases and cloud data warehouse (Snowflake, Databricks, Redshift, BigQuery, Synapse)
  • Experience with DevOps workflows like Airflow, MLFlow, Tecton and tools like GitHub
  • Experience in SaaS delivery
  • Contributions into open source communities and libraries
  • Experience with visualization tools like Tableau, PowerBI, and Excel
Join a team of passionate people committed to redefining the way business intelligence and AI is done.
For additional information, visit

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