Top Remote Data & Analytics Jobs

As a Data Scientist/Analyst at PayZen, you will develop statistical and machine learning models to improve patient engagement and financial processes. Responsibilities include collaborating with teams to optimize data strategies, designing AI/ML model infrastructure, and executing A/B tests to drive unbiased insights for better business outcomes.

As a Senior Data Engineer, you will be responsible for designing and implementing data solutions, managing ETL processes, and optimizing data warehousing strategies to support business analysis and reporting. You will collaborate with cross-functional teams to ensure data integrity and availability, leveraging Big Data technologies and AWS services to enhance data processing capabilities.

As a Principal MLOps Engineer, you will architect and optimize ML inference platforms, collaborate with teams for engineering solutions, and lead high-performance teams in developing efficient inference systems.

The Senior Analytics Engineer designs and optimizes data systems using Snowflake and dbt. Responsibilities include collaborating with sales, marketing, and finance analytics teams, developing data models, overseeing dbt projects, analyzing product performance, building financial models, and maintaining data quality and governance.

The Senior Director, Business Development role focuses on leading relationships with strategic accounts in the Data and AI vertical, ensuring service execution exceeds client expectations, identifying new business opportunities, and collaborating with teams to pitch services to clients.

The Senior Data Scientist will architect, design, and implement generative AI models for ASR and TTS applications, leveraging LLMs. Responsibilities include training and optimizing models, collaborating with cross-functional teams, and innovating existing models while staying updated on the latest advancements in generative AI.

As a Database Engineer, you will design, implement, and maintain database solutions for business operations and analytics. Collaborate with IT professionals, create and modify database objects, develop data pipelines, and optimize database performance while ensuring data confidentiality and maintaining documentation.