What is Contentstack?
Contentstack combines the best Content Management System (CMS) and Digital Experience Platform (DXP) technology. It enables enterprises to manage content across all digital channels and create inimitable digital experiences. The Contentstack platform was designed from the ground up for large-scale, complex, and mission-critical deployments. Recently recognized as the Gartner PeerInsights Customers' Choice for WCM, Contentstack is the preferred API-first, headless CMS for enterprises across the globe.
What Are We Looking For?
Contentstack is looking for a Data Scientist.
Role & Responsibilities:
- Analyze raw data, create and maintain optimal data pipeline architecture to improve data reliability and quality.
- Deep knowledge and hands-on experience in technologies across all data lifecycle stages.
- Experience and deep knowledge about Content Management Systems would be highly preferred.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources.
- Work closely with the Data Scientists and provide them with quality data for advanced analytics.
- Experience building and optimizing data pipelines, architectures and data sets.
- Strong analytical skills related to working with NoSQL databases and unstructured datasets.
Technical Requirements:
- At least 4+ years of experience as a data scientist with expertise on NLP and Deep Learning.
- Good knowledge on ETL and ELT tools and pipelines, Data APIs.
- Technical expertise with data models, data mining, and segmentation techniques
- Experience supporting, maintaining and monitoring data pipelines (real time & batch)
- Knowledge of programming languages (Python or Java).
- Experience with relational SQL and NoSQL databases (MongoDB).
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Degree in Computer Science, IT, or similar field. Master’s degree is a plus
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Demonstrated ability to develop advanced CI/CD pipelines in GitLab, Python, Apache Airflow (e.g. using dynamic data pipelines)
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Experience with one or more of MLOps tools: ModelDB, Kubeflow, Pachyderm, and Data Version Control (DVC) etc.
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Experience in Docker, Kubernetes, Jenkins, Spark (Highly preferred)
Skills:- CICD