Data Scientist for TruthTech

1-15 hours Fully remote work, 1 weekly e-meeting, collaboration via Teams for work, store code on Github, deploy to AWS, Truth Library is an AI-powered platform dedicated to delivering verified and insightful Q&A content. Our mission is to promote truthfulness and transparency by leveraging state-of-the-art AI models and cutting-edge technology. We are looking for a passionate and skilled Data Scientist to volunteer with us in further developing and deploying AI models that empower the Truth Library experience., * Develop, train, and fine-tune AI/ML models to support Truth Library’s Q&A system and content ranking algorithms.

• Optimize model performance for scalability and accuracy in real-world deployment.

• Collaborate with engineers and researchers to integrate AI models into our platform’s backend.

• Design and implement data processing pipelines and workflows.

• Analyze and process large datasets to extract actionable insights.

• Assist with the deployment and monitoring of AI solutions on AWS infrastructure.

• Participate in brainstorming and strategy sessions to align technical development with platform goals.

• Software and web development, * Proven experience with machine learning frameworks and libraries (TensorFlow, PyTorch, scikit-learn, etc.).

• Strong programming skills in Python or a similar language used in data science.

• Proficiency in building and optimizing models for NLP, classification, or ranking tasks.

• Hands-on experience with cloud platforms, preferably AWS (e.g., SageMaker, Lambda, EC2, S3).

• Familiarity with databases, especially PostgreSQL, and data handling in structured and unstructured formats.

• Knowledge of search technologies (e.g., OpenSearch, Elasticsearch) is a plus.

• Understanding of MLOps principles and best practices for model deployment.

• Excellent problem-solving skills and a strong analytical mindset.

Preferred Experience:

• 2+ years of experience in a data science or machine learning role.

• Experience deploying AI/ML models in a production environment, especially on AWS.

• Prior involvement in projects requiring natural language processing (NLP).

• Familiarity with graph-based algorithms or data visualization tools is a bonus.

• Contributions to open-source projects or publications in relevant domains.