Principal Data Scientist (Onsite in Houston)

Augment Professional Services • Houston, TX

1d • $40 - $40 • Onsite

About The Position

We are looking for a proactive Data Scientist with strong AI/ML and Large Language Model (LLM) expertise, particularly in time-series modeling. The ideal candidate should have experience analyzing diverse datasets, building machine learning models, and deploying AI solutions for business value. Responsibilities include developing time-series models from business data, with opportunities to work on deep learning, computer vision, natural language processing, LLMs, and multi-agent systems. You will design, train, and deploy scalable time-series models and turn data insights into actionable strategies.

Requirements

• Strong background in time-series modeling is essential.
• Excellent communication skills are highly valued.
• A solid foundation in time-series modeling and anomaly detection is required.
• Proficiency in Python and experience with time-series modeling techniques such as linear regression, random forest, and support vector machines are required.
• Strong communication abilities and a track record of collaborating with stakeholders and business owners are important.
• Curious & Innovative: Passionate about solving complex business problems using data and AI.
• Ownership & Initiative: Proactively drive projects from conception to deployment.
• Business Acumen: Understand how AI/ML solutions impact business goals and decision-making.
• Effective Communication: Ability to explain technical models and AI methodologies to non-technical audiences.

Nice To Haves

• A background in Generative AI and computer vision is helpful, but it is not required.
• Deep learning, Generative AI, computer vision, data engineering, and ML Ops experience is helpful but not required.
• Graduate degree (Master’s or Ph.D.) in a quantitative field (e.g., Computer Science, Data Science, Statistics, Engineering, Mathematics, Economics).
• Experience with time-series modeling and abnormal detection.
• Familiarity with deep learning and generative AI.

Responsibilities

• Data Analysis & Feature Engineering: Collect, process, and analyze structured and unstructured data, engineering relevant features to improve model performance.
• Develop, train, and optimize machine learning and deep learning models for time-series analysis and anomaly detection.
• LLM and Agent-based Application: Build AI solutions using LLMs, emphasizing prompt engineering, multi-agent systems, fine-tuning, and inference optimization.
• Business Impact & Decision Support: Translate complex data science methodologies into actionable insights, collaborating with stakeholders to drive business value.
• Data Storytelling & Visualization: Develop clear, compelling presentations and dashboards to communicate findings to non-technical stakeholders.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level