Senior Engineer I - Real World Data - Artificial Intelligence/Machine Learning (AI/ML)

Key Skills

Aartificial intelligence, Amazon Athena, Amazon RedShift, Amazon Simple Storage Service (S3), AWS, AWS Glue, Bitbucket, Confluence, Continuous Integration & Continuous Delivery - CI/CD, Data pipelines, Data science techniques, DynamoDB, Git, JIRA, Julia, Lambda, Machine learning techniques, Python Programming, R Programming, Scala Programming, SQL

Job Description

The Position

As a technical expert in their specialty within Novo Nordisk, the Senior Engineer will contribute to the research team’s effort towards exploring and creating new technology and being a world leader in the Data Engineering role. The Data Solutions Engineer will bring elements of appropriate data architecture and engineering, together with the infrastructure teams to translate data science solutions into highly available, scalable, reusable, consistent, secure and enterprise enabled systems and platforms, specifically in the applications of AI and Machine Learning (ML) applications. Moreover, the Sr. Data Engineer will contribute to the development, validation, and deployment of Artificial Intelligence/Machine Learning (AI/ML) algorithms and models, and work closely with other engineers to build AI/ML-fueled products.

Relationships

The Senior Solutions Engineer will report to the head of the related research area. Internal partners include data scientists, specialists, ML Ops engineers, software developers, system engineers, designers, IT professionals, technology scouts & partnership developers, and other functions across US and Denmark.

Essential Functions

• Generates and matures relevant ideas, concepts, and products that bring value to patients and the future Novo Nordisk business.
• Lead engineering efforts across multiple projects of varying complexities
• Work with various data science, ML, AI, imaging, bioinformatics, real-world evidence, and other research teams to build modern data-driven enterprise-ready solutions
• Interface with business partners to lead architecture and development of enterprise cloud-based data solutions and pipelines that feed into data science solutions
• Work with the data engineering, data science and data ownership teams to collect relevant data elements and implement data pipelines (data acquisition, preparation, cleaning, and consolidation) as an integral part of data science activity
• Work closely with various stakeholders to provide end-to-end support in data ETL and consumption
• Actively participates in cross-functional teams to develop AI and ML solutions
• Actively participates in virtual global team meetings regularly
• Collaborate with Data Scientists, engineers and/or scientists from other disciplines to build robust and sustainable enterprise data solutions that deliver AI/ML models 
• Collaborate with data scientists to design, code, train, test, deploy data models and pipelines that feed machine learning systems
• Prepare and present written and oral reports and proposals to peers and management

Physical Requirements

Up to 10% overnight travel required.

Qualifications

• Bachelor’s degree required, Master’s degree, or PhD is preferred. Degree within subject matter expertise preferred
• Bachelor’s degree with 5+ years’ relevant experience, or Master’s Degree with 3+ years’ relevant experience, or PhD with 0 years of experience can be considered
• Relevant experience includes:
• Experience ensuring the quality of the data in coordination with data analysts, data scientists and business partners (peer validation)
• Build and operationalize complex data solutions, correct problems, apply transformations, and recommending data cleansing/quality solutions
• Working knowledge of scripting languages (Python, R, Scala, Julia a plus)
• Familiarity with visualization tools (PowerBI, Tableau) and project management tools (JIRA, Confluence) a plus
• Demonstrated ability to proactively maintain up-to-date knowledge of the company's standards, industry-leading practices, and emerging technologies through self-driven initiatives.
• Preferred experience includes:
• AWS Certified Developer preferred 
• Experience working within compliance (e.g.: quality, regulatory - data privacy, GxP, SOX) and cybersecurity requirements 
• ​​​​​​​Experience working in life sciences/pharmaceutical industry 
• Perform analysis of complex sources to determine value and use and recommend data to include in analytical processes.
• Experience working within compliance (e.g.: quality, regulatory - data privacy, GxP, SOX) and cybersecurity requirements
• Perform analysis of complex sources to determine value and use and recommend data to include in analytical processes.
• Experience with SQL, DynamoDB, RedShift, EFS, EMR, EBS, ElastiCache and other relational/non-relational database technologies/concepts
• Experience with AWS data-related services such as Storage Gateway, CloudWatch, Glue, Athena, S3, Lambda, Data Pipeline, Data Migration, Step functions.
• Experience with CI/CD, basic ETL practices such profiling, cleansing, transforming, developing and documenting data structures, schemas and dictionaries.
• Proficiency in version control in git, GitHub, BitBucket, or similar tools.
• Demonstrated ability to work independently and in teams
• Detail oriented with excellent written and oral communication skills

We commit to an inclusive recruitment process and equality of opportunity for all our job applicants.

At Novo Nordisk we recognize that it is no longer good enough to aspire to be the best company in the world. We need to aspire to be the best company for the world and we know that this is only possible with talented employees with diverse perspectives, backgrounds and cultures. We are therefore committed to creating an inclusive culture that celebrates the diversity of our employees, the patients we serve and communities we operate in. Together, we’re life changing.

Novo Nordisk is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, gender identity, sexual orientation, national origin, disability, protected veteran status or any other characteristic protected by local, state or federal laws, rules or regulations.