Machine Learning Data Engineer Lead
This position reports to: Director, Data Science
ServiceNow is changing the way people work. With a service-orientation toward the activities, tasks and processes that make up day-to-day work life, we help the modern enterprise operate faster and be more scalable than ever before.
We’re disruptive. We work hard but try not to take ourselves too seriously. We are highly adaptable and constantly evolving. We are passionate about our product, and we live for our customers. We have high expectations and a career at ServiceNow means challenging yourself to always be better.
We have data! We need you to help translate it into actionable insights that help us grow even faster. We have a team of Data Scientists that serve our internal business departments in analyzing data from across the company to help them meet their goals.
Responsibilities:
Ensure the Machine Learning team meets the needs of our internal and external customers by supplying the data and processes needed to train, score, and scale robust ML models. You will:
- Lead and grow a team of exceptional ML Data Engineers, focusing on enhancing, measuring, and recognizing performance.
- Drive the technical and organizational roadmap for the ML Data Engineer team.
- Facilitate and participate in the preparation of ML data sets and scoring processes.
- Develop and maintain a knowledge of real-time and snapshotted data scources from across the company, as well as Analytics team members responsible for various sources.
- Work with the Data Integrations team and Data Architects to develop and implement key decisions on scalable, reliable, and cost-effective ML Data Engineering solutions, including Data Warehouse, Data Lakes, and ML Model interfaces
- Explore vendor solutions to streamline and expedite ML Data preparation, scoring processes, ML model evaluation, and ML Operations functions
- Implement data capture and optimization for tracking historic model performance, ML data input changes over time, and ML score changes over time
- Develop and support the ML portion of the Enterprise Data Platform strategy to maximize the distribution of ML predictions and recommendations, including API-based ML scoring and data warehouse-based access
- Incorporate workflows into ML Data Engineering processes, to automate, monitor, and produce alerts
- Guide the ML Data Engineer team in implementing performance tuning and query optimization
- Act as a resource to the Machine Learning team with regards to Data Lifecycle Management
- Represent ML deployments in the Analytics Review Committee to shepherd Machine Learning projects through the process
- Collaborate with Analytics team members to promote the ML model results available to the business, the value that the results represent, the underlying table formats and the table contents
Requirements:
- 3+ years of experience managing a team of data engineers.
- Bachelor’s degree or equivalent in Computer Science, Computer Engineering, Information Systems or similar. Masters degree preferred.
- 7+ years of documented experience as a SQL developer in data warehouse technologies.
- Experience using Airflow, Spark, and/or Python in a commercial setting.
- Experience with assembling and maintaining big data/very large ML data sets
- Strong communication, presentation, and interpersonal skills. Ability to influence stakeholders and build cross-functional alignment.
Desired Skills:
- SAP HANA, Databricks, Azure Data Lakes experience preferred.
- Knowledge of business data and processes from more than one business department.
- Experience with the ServiceNow platform, with an IT background, product usage experience, or with Software-as-a-Service experience
ServiceNow is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, or veteran status. If you are an individual with a disability and require a reasonable accommodation to complete any part of the application process, or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you may contact us at [email protected] for assistance.