Data Science Manager II

• Higher level relevant degree may substitute for experience.
• Hands-on experience with ontology tools such as Fabric, Foundry, Oonto Me, OWLGrEd, Protégé, etc
• Previous experience using scripting languages:
  Python, PySpark, Scala, R, etc.

Lead SNC’s enterprise business integrated AI and Business Intelligence initiatives by designing and deploying scalable, ontology-driven solutions. This role drives digital transformation through advanced analytics, semantic data modeling, and integration of cutting‑edge tools.

The position is designed to drive SNC’s transformation and data‑driven enterprise strategy. It emphasizes:
Business Intelligence (BI):
Leveraging advanced analytics to improve decision‑making and operational efficiency. AI at Scale:
Deploying scalable AI solutions across multiple business units, ensuring integration with SNC’s enterprise architecture. Ontology‑Based Data Management:
Using semantic models to unify data sources and enable interoperability across platforms.

As SNC's corporate team, we provide the company and its business areas with strategic direction and business support spanning executive management, finance and accounting, operations, human resources, legal, IT, information security, facilities, marketing, and communications.

• Product Ownership:
  Own and optimize BI and AI platforms (e.g., Palantir Foundry, Azure AI Foundry) to enable scalable, production‑ready solutions.
• Ontology Development:
  Build and maintain semantic models to unify data across systems, supporting interoperability and advanced analytics.
• Tool Integration:
  Implement and manage data ecosystems using Microsoft Fabric, Foundry, OpenPDM, and Neo4J for graph‑based knowledge representation.
• Business Intelligence Leadership:
  Drive enterprise‑wide BI initiatives, enabling actionable insights and data‑driven decision‑making.
• Innovation & Culture:
  Promote BI versus AI literacy and innovation through programs and internal enablement that utilizes the right expertise within SNC and external partners.

• Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field.
• 10+ years of experience in data science, with at least 2 years in a leadership role.
• Higher level relevant degree may substitute for experience.
• Relevant experience can be considered as a substitute for the required educational qualifications. In the absence of a degree, a minimum of 14 years of related experience is required.
• Proven experience in AI/ML deployment at scale and BI strategy.
• Expertise in ontology‑based data management and graph technologies.
• Hands‑on experience with ontology tools such as Fabric, Foundry, Oonto Me, OWLGrEd, Protégé, etc.
• Strong leadership and stakeholder engagement skills.
• Extensive experience with advanced machine learning algorithms and data modeling.
• Experience managing multiple projects and teams.
• Proficiency in data visualization tools (e.g., Tableau, Power BI).
• Strong ability to prioritize and communicate to technical and non‑technical audiences.
• Solid applied statistics skills, such as distributions, statistical testing, regression, etc.
• Understanding of machine learning techniques and algorithms, Large Language Models (LLMs)/Generative AI.

• Experience with big data technologies (e.g., Hadoop, Spark).
• Certifications in data science or related fields (e.g., Certified Analytics Professional).
• Experience with cloud platforms (e.g., AWS, Azure).
• Previous experience using query languages such as SQL, Hive, Pig, etc.
• Previous experience using scripting languages:
  Python, PySpark, Scala, R, etc.
• Experience with common data science toolkits, such as R, Weka, Num Py, Mat Lab, AWS Sage Maker, etc.
• Experience building data pipelines and driving ETL design decisions.
• Experience with Azure, AWS Data Warehousing: AWS RDS (Postgre
  
  SQL), Redshift.
• Experience with No
  
  SQL databases, such as Mongo
  
  DB, Cassandra, HBase, Amazon Dynamo
  
  DB.

• Ability to work on a computer for extended periods.
• Frequent communication with team members and stakeholders.
• Occasional travel may be required.
• Ability to work in an office or hybrid environment.
• Must be able to…