4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience
MS in Computer Science, Applied Mathematics, Statistics, Physics or equivalent work or industry experience
4 plus years of experience in end-to-end application development, data exploration, data pipelining, API design, optimization of model latency
Expertise in MLOps frameworks and hands on experience in MLOps tools preferably Google Vertex ai
2 plus years of experience deploying Machine Learning algorithms into production environments - including model and system monitoring and troubleshooting
Highly proficient programming in Scala and/ or Python/Pyspark
Good understanding of Big Data tech - specifically Hadoop, Kafka, Spark
Experience in handling streaming data and real-time forecasting solutions deployment
Solid understanding of data analysis techniques, including data cleaning, preprocessing, and visualization
Demonstrated ability collaborating with data scientists, software engineers and product managers to understand the business requirements and translate to machine learning solutions at scale
Excellent communication skills with the ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives Self-driven and results oriented - able to meet tight timelines
Motivated, team player with ability to collaborate effectively across global team
Understanding of retail industry and pricing concepts is added advantage
Bonus Points:
Extensive experience with Deep Learning frameworks TensorFlow, Pytorch or Keras
PhD in Computer Science, Applied Mathematics, Statistics, Physics or related quantitative field
Extensive experience developing highly distributed ML systems at scale
Familiarity with Vertex AI and Cloud ML ecosystem will be desirable
Experience in mentoring the junior team members ML skillset and career development
