Eyeota is looking for an exceptional Data Scientist who is passionate about data and motivated to build large scale machine learning solutions to shine our data products. This person will be contributing to the analytics of data for insight discovery and development of machine learning pipeline to support modeling of terabytes of daily data for various use cases.
- 2+ years relevant working experience
- Master/Bachelors in computer science or engineering
- Working knowledge of Python, Spark/Pyspark, SQL
- Experience working with large-scale data
- Experience in data manipulation, analytics, visualization, model building, model deployment
- Proficiency of various ML algorithms for supervised and unsupervised learning
- Experience working in Agile/Lean model
- Exposure to building large-scale ML models using one or more of modern tools and libraries such as AWS Sagemaker, Spark ML-Lib, Tensorflow, PyTorch, Keras, GCP ML Stack
- Exposure to MLOps tools such as MLflow, Airflow
- Exposure to modern Big Data tech such as Cassandra/Scylla, Snowflake, Kafka, Ceph, Hadoop
- Exposure to IAAS platforms such as AWS, GCP, Azure
- Experience with Java and Golang is a plus
- Experience with BI toolkit such as Superset, Tableau, Quicksight, etc is a plus
Eyeota empowers brands with the solutions they need to confidently identify, reach, and engage their best audiences. By combining privacy-safe and qualified technologies with data expertise, we help businesses to understand the potential of their data assets to transform their marketing initiatives, customer programs, and business revenues. We are a trusted global partner to our customers providing data onboarding, first-party data enrichment, identity resolution and audience engagement solutions that help to connect consumers with the right brands and products in omnichannel environments.
Eyeota provides a fast-paced, dynamic and fun workplace filled with curious, inventive and problem-solving individuals. We have a truly global footprint, with our headquarters in Singapore and offices in Australia, Germany, the United States, United Kingdom and India. We are committed to investing in our people, products and infrastructure to deliver diverse, cutting-edge data solutions th