American Bureau of Shipping
What You Will Do
Apply advanced data science concepts to deliver data-driven digital offerings and insights using Databricks Lakehouse architecture.
Utilize modern machine learning methods and domain understanding to support the creation of new products and services, leveraging MLflow for experiment tracking and model lifecycle management.
Collaborate with data and analytics teams and cross-functional departments such as digital, services, class, and engineering to build scalable ML solutions and deliver actionable insights.
Write independent source code in Python, PySpark, and SQL, validate and test models, and use Databricks Feature Store for consistent feature reuse and governance.
Design and implement robust data architectures using Delta Lake and manage data assets securely via Unity Catalog and Azure Data Lake.
Combine Agile methodologies with data science practices to build advanced analytics and AI products using Databricks Workflows and Azure ML Pipelines.
Develop, test, deploy, and maintain machine learning and AI models using Databricks Runtime for ML, ensuring scalability, performance, and governance.
Lead the data-driven decision-making process, from data collection and analysis to implementation and monitoring of solutions using Databricks Jobs, CI/CD pipelines, and Azure DevOps.
Support organizational decision-making based on the results of analytics efforts, ensuring traceability and governance via Unity Catalog and Azure Purview.
Work independently on data engineering, preprocessing, and preparation tasks using Databricks Notebooks, SQL Warehouses, and Azure Synapse Analytics.
Mentor data scientists, ASPIRES, and interns, providing guidance and support in their professional development and technical growth.
Evaluate and partner with external customers, vendors, university relations, and other teams to drive innovation and collaboration.
Stay current in the field of AI and advanced analytics, with a focus on innovations within the Databricks, Azure, and OpenAI ecosystems, including LLMs, GenAI, and MLOps.
Develop and deploy scalable and interpretable data products per business-defined requirements using Databricks Repos, Model Serving, and Azure Machine Learning.
What You Will Need Education and Experience
Bachelor’s Degree in Data Science, Information Systems, Computer Science, Engineering or other relevant field with relevant experience.
Required -5 or more years of experience in Data Science, Information Systems, Computer Science, Engineering, or other field with relevant experience.
Preferred -Master’s Degree in Data Science, Data Analytics, Information Systems, Computer Science, Engineering or other relevant field.
Preferred - 1 or more years of work experience as a Sr Data Scientist, demonstrating leadership on projects involving applied AI and Machine Learning.
Knowledge, Skills, and Abilities
Strong written and verbal communication skills.
Strong written and verbal communication skills, with the ability to translate complex data into actionable insights.
Experienced in working with cross-functional teams to understand business challenges and deliver data-driven solutions.
Proficient in machine learning, data mining, statistical analysis, and applied AI methods using Databricks, Azure ML, and Dataiku.
Skilled in developing scalable ML solutions and translating analytics into business impact.
Advanced proficiency in Python, PySpark, SQL, and tools such as Jupyter, VS Code, and MLflow.
Experience with database technologies and architectures including Delta Lake, Azure Data Lake, SQL Warehouses, and Synapse Analytics.
Hands-on experience with AutoML platforms such as Dataiku, and familiarity with Azure AutoML.
Deep understanding of Azure Cloud resources, including Azure Machine Learning, Azure DevOps, Azure Cognitive Search, and Azure OpenAI.
Familiarity with Generative AI solutions, Large Language Models, and NLP frameworks like Hugging Face Transformers.
Ability to develop a working knowledge of ABS Rules, Guides, statutory regulations, and related instructions, as well as the ABS Employee Safety Policy.
It Would Be Nice If You Have
Career Essentials in Generative AI by Microsoft and LinkedIn
Build Your Generative AI Productivity Skills with Microsoft and LinkedIn
Azure AI Fundamentals
Azure Data Scientist Associate
Azure AI Engineer Associate/Databricks Certification
Reporting Relationships Reports to Senior Manager on Data and Analytics team
#J-18808-Ljbffr
Apply advanced data science concepts to deliver data-driven digital offerings and insights using Databricks Lakehouse architecture.
Utilize modern machine learning methods and domain understanding to support the creation of new products and services, leveraging MLflow for experiment tracking and model lifecycle management.
Collaborate with data and analytics teams and cross-functional departments such as digital, services, class, and engineering to build scalable ML solutions and deliver actionable insights.
Write independent source code in Python, PySpark, and SQL, validate and test models, and use Databricks Feature Store for consistent feature reuse and governance.
Design and implement robust data architectures using Delta Lake and manage data assets securely via Unity Catalog and Azure Data Lake.
Combine Agile methodologies with data science practices to build advanced analytics and AI products using Databricks Workflows and Azure ML Pipelines.
Develop, test, deploy, and maintain machine learning and AI models using Databricks Runtime for ML, ensuring scalability, performance, and governance.
Lead the data-driven decision-making process, from data collection and analysis to implementation and monitoring of solutions using Databricks Jobs, CI/CD pipelines, and Azure DevOps.
Support organizational decision-making based on the results of analytics efforts, ensuring traceability and governance via Unity Catalog and Azure Purview.
Work independently on data engineering, preprocessing, and preparation tasks using Databricks Notebooks, SQL Warehouses, and Azure Synapse Analytics.
Mentor data scientists, ASPIRES, and interns, providing guidance and support in their professional development and technical growth.
Evaluate and partner with external customers, vendors, university relations, and other teams to drive innovation and collaboration.
Stay current in the field of AI and advanced analytics, with a focus on innovations within the Databricks, Azure, and OpenAI ecosystems, including LLMs, GenAI, and MLOps.
Develop and deploy scalable and interpretable data products per business-defined requirements using Databricks Repos, Model Serving, and Azure Machine Learning.
What You Will Need Education and Experience
Bachelor’s Degree in Data Science, Information Systems, Computer Science, Engineering or other relevant field with relevant experience.
Required -5 or more years of experience in Data Science, Information Systems, Computer Science, Engineering, or other field with relevant experience.
Preferred -Master’s Degree in Data Science, Data Analytics, Information Systems, Computer Science, Engineering or other relevant field.
Preferred - 1 or more years of work experience as a Sr Data Scientist, demonstrating leadership on projects involving applied AI and Machine Learning.
Knowledge, Skills, and Abilities
Strong written and verbal communication skills.
Strong written and verbal communication skills, with the ability to translate complex data into actionable insights.
Experienced in working with cross-functional teams to understand business challenges and deliver data-driven solutions.
Proficient in machine learning, data mining, statistical analysis, and applied AI methods using Databricks, Azure ML, and Dataiku.
Skilled in developing scalable ML solutions and translating analytics into business impact.
Advanced proficiency in Python, PySpark, SQL, and tools such as Jupyter, VS Code, and MLflow.
Experience with database technologies and architectures including Delta Lake, Azure Data Lake, SQL Warehouses, and Synapse Analytics.
Hands-on experience with AutoML platforms such as Dataiku, and familiarity with Azure AutoML.
Deep understanding of Azure Cloud resources, including Azure Machine Learning, Azure DevOps, Azure Cognitive Search, and Azure OpenAI.
Familiarity with Generative AI solutions, Large Language Models, and NLP frameworks like Hugging Face Transformers.
Ability to develop a working knowledge of ABS Rules, Guides, statutory regulations, and related instructions, as well as the ABS Employee Safety Policy.
It Would Be Nice If You Have
Career Essentials in Generative AI by Microsoft and LinkedIn
Build Your Generative AI Productivity Skills with Microsoft and LinkedIn
Azure AI Fundamentals
Azure Data Scientist Associate
Azure AI Engineer Associate/Databricks Certification
Reporting Relationships Reports to Senior Manager on Data and Analytics team
#J-18808-Ljbffr