Job Location: United States
Job Detail:
*** This role is an initial 90 day full time (40 hrs pw) contractor (C2C) opening, with a view to moving to a Perm (Full Time) position afterwards (based on work and level of expertise) ***
Are you excited in joining a high growth, venture backed tech start-up, and become an integral part of an expert, nimble Data Science team, where you’ll learn to thrive in a fast-paced environment with tons of cool and hard to solve problems?
Our Client is a high growth startup in the Data Science as a Service (DSaaS) space for e-commerce next gen brands, aparrel, and retail.
They have built a cutting-edge AI platform purpose-built to help modern commerce brands grow and retain customers through deeper application of data. This provides brands that struggle to derive value from their first party data and lack robust Data Science talent with a solution that uses the latest algorithmic techniques and advancements in predictive analytics to enhance business decisions and customer experiences.
What does our Client provide?
- Brands with a microscopic understanding of their customers based on individualized product preferences and geographical factors.
- Intelligence driven data, which is used by all stakeholders across all functions, will inform, enhance, and optimize their decision-making
- Resulting in an ever-optimizing flywheel that drives the acquisition and retention of high-value customers.
Our Client seeks a Data Engineer (3+ yrs. commercial experience) who has experience working across the tech stack, including ETL across ingestion, data warehouse modeling and ML production.
Key responsibilities will include:
- Managing compute clusters for ML training, inference and development
- Designing and building out our data warehouse for scalability as we onboard our next wave of customers
- Creating tooling and infrastructure that abstract compute and storage in ML development workflows
- Onboarding new customers’ data into our pipelines and making required adjustments as necessary
- Building automation and CI/CD pipelines for developing and deploying new machine learning models
Key qualifications should include:
- Confidence and demonstrable expertise across the entire stack
- High aptitude for problem solving
- Programming Languages: Python, SQL
- Cloud based software: AWS (+Sagemaker), GCP (+BigQuery), Airflow, dbt, DynamoDB, Lambda
- Knowledge of Docker, Terraform, Kubernetes is a plus
You will be developing and scaling the infrastructure behind the development, testing, and deployment of their machine learning models.
- Culturally, you’ll bring prior experience at another high growth, venture backed tech and/or retail/e-commerce start-up (ideally as part of a small, nimble, cross functional team). You will seek out and thrive in a fast-paced environment with heaps of ambiguity and rapidly changing conditions.
- As a Data Engineer, you will habitually think in a creative / out of the box way to approach problems and challenge the status quo with ‘first principle thinking’ in everything that you do.
- An ideal candidate will also be able to read ML code and have a comprehensive understanding of the outcomes we are trying to achieve with each ML model, as well as the tactical elements of how to implement and operationalize them.
- You value simplicity – rather than opting for a complex, highly-architected solution, you bias toward developing clean, efficient designs and processes.
- You are a self-starter who is detail oriented, balancing the ability to move quickly while ensuring data is transformed correctly at each step, avoiding the potential for larger issues downstream.
- You are comfortable developing solutions by taking the quickest path possible and are at ease continuously iterating in quick cycles with an eye toward reliability and scalability.
- This role will report directly into the CTO based in New York.
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