Principal Data Scientist - Machine Learning

AvePoint•Seattle, WA

55d•Hybrid

About The Position

Beyond Secure. AvePoint is the global leader in data security, governance, and resilience, going beyond traditional solutions to ensure a robust data foundation and enable organizations everywhere to collaborate with confidence. Over 25,000 customers worldwide rely on the AvePoint Confidence Platform to prepare, secure, and optimize their critical data across Microsoft, Google, Salesforce, and other collaboration environments. AvePoint's global channel partner program includes approximately 5,000 managed service providers, value-added resellers, and systems integrators, with our solutions available in more than 100 cloud marketplaces. To learn more, visit www.avepoint.com. At AvePoint, we are committed to investing in our people. Agility, passion and teamwork set us up to do our best work and foster a culture where you are empowered to craft your career, make an impact, and own (y)our future. Unleash the power of you! We are seeking an analytical and innovative Data Scientist to join our Data & AI team. You will play a key role in developing and deploying advanced machine learning models to solve real-world business challenges. Your efforts will help optimize data pipelines, extract actionable insights, and shape the future of intelligent solutions at AvePoint.

Requirements

10+ years of hands-on machine learning experience, including building, evaluating, and streamlining data-driven models for business use.
Proficiency with Python and major ML/data libraries (e.g., Pandas, Scikit-learn, TensorFlow, PyTorch).
Strong background in data wrangling, cleansing, feature engineering, and ETL pipeline development.
Practical experience deploying models in a cloud or distributed environment.

Nice To Haves

Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Statistics, or related field (PhD not required, but a strong plus).

Responsibilities

Design, build, and deploy machine learning models leveraging structured and unstructured data.
Shape and engineer data pipelines for optimal model performance and production-grade scalability.
Collaborate cross-functionally with engineers, researchers, and product teams to define requirements and deliver impactful AI/ML solutions.
Analyze experimental data, conduct model validation, and continuously improve accuracy and robustness.
Document methodologies and results, presenting findings to both technical and non-technical stakeholders.
Stay up-to-date with the latest advancements in machine learning and data science best practices.
Support operationalizing models within AvePoint's ecosystem, ensuring responsible data handling and compliance.