Top Data Engineer Jobs in Boston, MA

Lead Data Specialist supervising a team within Data Management, managing day-to-day operations, interacting with internal study teams and sponsors, ensuring database integrity, and executing SQL data scripts.

Experiment with state-of-the-art algorithms to improve knowledge retrieval and search efficiency, develop NLP and Gen AI models to enhance customer support effectiveness, collaborate with teams to drive impactful solutions, and monitor model performance.

Primary client-facing role overseeing consulting projects for a diverse, growing client base. Responsibilities include client lifecycle management, data model expansion, report development, client training, and team management. Must have 3-5 years of related business experience.

As a Director in the Products & Technology Risk and Quality team at PwC, responsibilities include managing technology and data risks, analyzing marketplace trends, developing networks, and upholding business conduct. The role requires strong communication, critical thinking, and decision-making skills, impacting the firm's revenue and reputation.

As a Senior Machine Learning Engineer at Movable Ink, you will work on advancing the core machine learning solution and infrastructure, focusing on recommender-system related challenges and collaborating with engineering teams to improve ML development experience. The base pay range for this position is $180,000 - $220,000 USD/year. Stock options, commission pay, and benefits are also provided as part of the compensation package.

Hiring a Principal Machine Learning Engineer/Data Scientist at Chewy to work on model development, optimization, tuning, and experimentation. Responsible for collaborating with cross-functional teams to enhance customer experience through personalized recommendations and search functionalities. Requires advanced degree or 10+ years of experience in data science and machine learning.

Build, orchestrate, and monitor model pipelines including feature engineering, scaling machine learning algorithms, and implementing ML Ops. Write production-ready code, collaborate with client teams, and contribute to researching latest technologies.