Applied Machine Learning Scientist

October 10

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Workiva

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Government Reporting • Internal Controls • Section 16 • SEDAR Reporting • SOX

1001 - 5000

💰 $689.3k Venture Round on 2014-10

Description

• The Applied Scientist at Workiva will contribute to well-defined machine learning tasks, including data processing, running predefined machine learning experiments, and writing production-level code to support ML features. • With periodic guidance from a technical leader, the Applied Scientist will independently contribute to team projects by developing and deploying ML models and pipelines to production. • This role involves thorough documentation of experiments to ensure clear records of processes and results, following best practices for ML development. • The ideal candidate will bring a strong foundation in machine learning, coding, and collaboration within a team environment.

Requirements

• Familiarity with machine learning concepts and tools (e.g., supervised learning, neural networks, model evaluation) • Experience with Python or similar programming languages used in ML development • Understanding of data structures, algorithms, and statistical methods commonly used in machine learning • Experience with cloud-based environments (AWS, GCP, or similar) is a plus • Familiarity with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) • Strong communication skills, with the ability to explain technical concepts to non-technical team members • Eagerness to learn and apply new technologies and techniques in a fast-paced environment • 2 years of Data Science experience or; or an advanced degree without experience • Proficiency in the machine learning development cycle, toolsets, and applying ML solutions to real-world problems • Familiarity with Generative AI and relevant development patterns • Experience with data preprocessing, model deployment, and working with data pipelines • Familiarity with Generative AI or similar modern AI techniques is a plus • Knowledge of version control systems (e.g., GitHub) and experience in Agile or Sprint environments • Experience working in Agile/Sprint environments and debugging complex systems or applications • Knowledge of web protocols (HTTP), databases, performance tuning, and production-level testing • Strong communication and organizational skills for managing multiple projects and meeting deliverables effectively

Benefits

• A discretionary bonus typically paid annually • Restricted Stock Units granted at time of hire • 401(k) match and comprehensive employee benefits package