Data Engineer - USQ Squad
Increasing your teammates’ productivity by improving their access to data and information. This includes building data pipelines, setting up data stores, and creating infrastructure to facilitate Machine learning model training and evaluation.
Empower Machine Learning Engineers and Data Scientists to develop models more quickly & effectively.
- Building data transformation pipelines with humans in the loop: in order to increase the frequency of our ML models updates, you will be in charge of automating and expanding a semi-manual datasets generation pipeline, including tagging jobs preparation, scheduling and post-processing.
- Data distribution shift monitoring: you will design a system capable of detecting changes in our data distribution, as well as the apparition of unknown image quality issues by monitoring the behavior of our ML models in production.
- Dataset growth strategy: you will use your developed expertise of our business data and system monitoring tooling to help identify valuable zones of expansion of our automated solution.
- Datasets versioning management: you will be in charge of managing and documenting datasets versions of an ecosystem of highly dependent and changing datasets.
- Live event data streaming and providing streaming analytics which will help in taking business decisions.
- Data volatility management: you will help develop solutions to stabilize our datasets in an environment where data retention is time limited.
- System performance analysis: you will support your team and the organization to answer questions related to the behavior of our automated system on particular transactions and data buckets by diving into the data and our models. You will use your advanced python skills to produce targeted performance metrics that will lead you from a metric to problematic examples.
- Automating processes that would provide data to stakeholders regarding different services.
Ideal Experience and Qualifications
- Building data pipelines in dynamic and changing environments
- Performing data analysis and data dives
- Proficiently leveraging cloud environments
Great to have Experience and Qualifications
- Familiarity with privacy by design
- Serverless data engineering
Key Characteristics and Attitudes
In a recent global survey these attributes were valued by Jumios in all locations and functions - we firmly believe in hiring for attitude as well as skill.
- Friendly and supportive
- Adaptable and flexible
- Articulate and persuasive
- High IQ and EQ
- Ability to handle ambiguity
- Know how to seek out information
- Effective communication within and outside the team
- Curious and coachable
- Commercially Aware
- Resilient and tenacious
- Big picture and the detail
- IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation
Engineers benefit from learning credit to strengthen their professional development. We are a fast growing company that nurtures individuals’ growth and career development.
Jumio AI Labs in Montreal is one of three R&D centres at Jumio, alongside Vienna, Austria and Bangalore, India. Located in downtown Montreal, we focus on R&D in computer vision as well as general Machine Learning. We deliver components that power Jumio’s market leading products. Jumio Montreal is a diverse team of engineers from a variety of countries that all enjoy collaboration, knowledge sharing, being curious and driving advancements in Machine Learning and ID Verification. Our Office is also a cultural hub where we celebrate unity in diversity through team-building activities and highlight every cultural event happening around the world.
Jumio is the future for online and mobile ID verification. We are the largest and fastest growing company in the ID verification space. With a global footprint, we’re expanding the team to meet strong client demand across a range of industries including Financial Services, Travel, Sharing Economy, Fintech, Gaming, and others.
Jumio is a collaboration of people with different ideas, strengths, interests and cultures. We welcome applications and colleagues from all backgrounds and of all statuses.