What are the responsibilities and job description for the Principal Data Scientist (Onsite in Houston) position at Augment Professional Services?
Job Description -
Non-negotiable Must Have Requirements:
Non-negotiable Must Have Requirements:
- Strong background in time-series modeling is essential.
- Excellent communication skills are highly valued.
- A background in Generative AI and computer vision is helpful, but it is not required.
- Data Scientist – AI/ML Focus
- Onsite mandatory Mon-Thur – Houston, TX
- 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.
- 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.
- 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.
- Deep learning, Generative AI, computer vision, data engineering, and ML Ops experience is helpful but not required.
- 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.
- 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.
Salary : $40