Sr. Machine Learning Engineer (Python)

Description Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Mac...

Description

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best analytics global consulting team in the world.

An Engineer with 5+ years of experience and will ensure data quality, creation of new data pipelines, optimization and management of existing data pipelines, ingestion and curation of data sources for analytical purposes, and transformations of structured and unstructured data into formats suitable for machine learning and advanced analytics. The Engineer will work on deployment and making sure products are production-ready and function smoothly.

Requirements

• Strong Python engineering skills and SQL skills
• Ability to Clean, easy to maintain, modify and support code
• Proficient in Python best practices, logging and strong debugging skills
• Understanding of Python environments, package management
• Strong basic SQL knowledge, able to read and understand SQL handed off
• Able to do standard SQL joins, filtering, etc
• Experience in Distributed computing frameworks such as Spark and Dask
• Able to work independently and ask for guidance when needed
• Strong communication skills and delivery focused
• Familiar with git source control
• Understanding the pre-processing analytical methods is a plus
• Bachelor's degree in Computer Science or closely related field
  

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, challenging, and entrepreneurial environment, with a high degree of individual responsibility.