Why This Role Stands Out
This remote Data Scientist role at Hexacorp offers a fantastic opportunity to leverage cutting-edge machine learning techniques to solve impactful business problems across diverse product teams, fostering significant professional growth. You'll thrive here if you possess strong analytical and communication skills, a passion for developing innovative solutions, and expertise in advanced ML models and Big Data technologies. Apply today to join a dynamic, forward-thinking team!
Quick Overview
Job Description
Title: Data Scientist/Machine Learning Scientist
Location: Remote (Atlanta, GA)
Contract (W2)
Job Description:
- The AI and Data Science team is centralized across the entire organization.
- Data Scientists work with various product teams across various business units to define high-impact business problems, solve them using novel techniques, and execute and monitor them throughout their lifecycle.
- They possess advanced analytical skills, in addition to their exceptional oral and written communication abilities.
- They effectively utilize appropriate statistical and Machine Learning models and techniques to solve various business problems.
- Additionally, they collaborate with various departments to identify opportunities for process improvement and developing analytics use-cases.
- They also have advanced knowledge of different techniques such as: Random Forests, Gradient Boosting or XGBOOST, Support Vector Machines (SVMs), Deep Learning, Clustering techniques such as Kmeans or DBSCAN, etc.
- They are highly technical and require advanced skills with computers and proficiency with Big Data tools and technologies such as SQL, Python/Scala, PySpark and SparkR.
- Data Scientist is required to evaluate accuracy and quality of data sources, as well as the designed models.
- Also, they need to stay up to date with the latest models and changes in the technology.
Qualification:
Bachelor’s, master’s or Ph.D. in Computer Science, Electrical Engineering, Machine Learning, Statistics or related field
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