Highlightta

Highlightta

Data Scientist

Canada

Sponsorship not specifiedDetected 4 days ago
PythonData StructuresSQLSnowflakeAWSCloud PlatformsMachine LearningData EngineeringData ScienceNLPLLMsAgentic AIMLOpsSalesforceCRMCommunicationPipeline Integrity

About the role

  • We are on a transformative journey to harness the power of artificial intelligence and machine learning for the social good sector.
  • We're looking for a foundational member of our data team to architect the data models and intelligence layer that enable AI agents to automate business processes across our products.
  • Your work will provide the critical foundation for autonomous decision-making and automated reporting - strengthening Neon One's technological foundation and empowering our customers to significantly increase their social impact through data-driven automation.

Responsibilities

  • Data Modeling & Architecture: Dive deep into large, disparate datasets from across our application platform to design relational, dimensional, and analytical data models.
  • Infrastructure & Pipeline Integration: Partner closely with our Data Engineer and Salesforce architects to define data requirements, ensure pipeline integrity, design schemas, and operationalize data flows - including implementing zero-copy data federation between our cloud environment (Snowflake/AWS) and enterprise CRM systems.
  • Deliver Platform Value: Develop the underlying data layers, views, and infrastructure that power reports and dashboards, delivering insights at an aggregate level (industry trends) and on a per-customer basis.
  • Familiarity with building data products, multi-tenant databases, or data isolation in a SaaS environment.
  • We use AI tools to support our recruitment process, including helping us organize applications and identify early matches based on role criteria.

Requirements

  • Demonstrated proficiency in Python (or similar languages) and associated libraries for heavy data manipulation, ETL/ELT processes, and system integration.
  • Demonstrated ability to work as a highly autonomous self-starter, comfortable with data ambiguity and taking ownership of infrastructure projects from start to finish.
  • Exceptional communication skills, with the ability to articulate complex infrastructure and data modeling concepts to diverse stakeholders effectively.
  • Data Programming: Demonstrated proficiency in Python (or similar languages) and associated libraries for heavy data manipulation, ETL/ELT processes, and system integration.
  • Experience with Salesforce Data Cloud (Data 360), Mulesoft, or architecting data structures specifically optimized for autonomous AI agents (e.g., Agentforce).
  • Experience with Natural Language Processing (NLP) techniques or engineering pipelines for Large Language Models (LLMs) and Vector Databases.

Nice to have

  • direct experience with AWS SageMaker and automated deployment workflows is highly preferred.

Benefits

  • Model Deployment & MLOps: Design, build, train, and validate machine learning models, with an emphasis on packaging, deploying, and monitoring these models efficiently in production at scale.
  • Cloud ML Platforms & MLOps: Hands-on experience building, training, and deploying machine learning models using a major cloud ML platform
  • Education: A Bachelor's degree in a technical field such as Computer Science, Software Engineering, Information Systems, or a related quantitative discipline.

Company info

  • Neon One on LinkedIn https://www.linkedin.com/company/neonone/
  • HighlightTA on LinkedIn https://www.linkedin.com/company/highlightta/
  • At Neon One, our values are how we show up every day.
  • We make good happen by putting empathy and passion at the center of our work, using technology to uplift mission-driven organizations.
  • We stand for our customers, act with care and intention in every decision, own the solution, and grow together.
  • We innovate fearlessly, always exploring new ways to support our community and each other.
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This listing is sourced directly from Highlightta's careers page and normalized into a canonical job model.