Principal Scientist, Data

Qualifications

• Hands-on experience with AI/ML, NLP, LLM applications (GPT/BERT/LangChain), predictive modeling, and deep learning
• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face)
• Advanced SQL skills and experience integrating data from multiple sources
• Experience with Snowflake, AWS (SageMaker, S3, Redshift), and automated ML pipelines
• Strong understanding of version control (Git) and collaborative development
• Highly curious, innovative, and growth-oriented mindset
• Ability to drive projects independently from ideation to deployment
• Strong business acumen with the ability to align technical output to business needs
• Excellent communication skills with the ability to simplify technical concepts
• Master’s or Ph.D. in Computer Science, Data Science, Mathematics, Statistics, Engineering, or another quantitative discipline
• Experience using BI or model-monitoring tools (Power BI, Dash, Streamlit)
• Familiarity with reinforcement learning or agent-based AI systems

Responsibilities

• The ideal candidate will excel at blending complex datasets, building predictive and statistical models, and delivering AI-driven solutions that create measurable business impact
• This role will work hands-on with advanced LLMs and modern ML frameworks to design, train, deploy, and optimize AI applications within a real-world operational environment
• You will partner closely with business and technical stakeholders to translate data science into clear, actionable strategies
• AI/ML Model Development: Design, train, fine-tune, and evaluate machine learning and deep learning models—including LLMs—for predictive analytics and automated decision-making
• Data Engineering & Feature Development: Collect, clean, and analyze structured and unstructured data; engineer features to improve model accuracy and efficiency
• NLP & Agent-Based AI Applications: Build LLM-powered solutions using prompt engineering, fine-tuning, inference optimization, and agent-based architectures
• Business Decision Support: Convert statistical and ML findings into practical insights and recommendations that support strategic decisions
• End-to-End Deployment (MLOps): Implement, deploy, and monitor ML models using best practices for reliability, scalability, and performance
• Data Storytelling & Communication: Create dashboards, visualizations, and presentations that clearly communicate insights to non-technical stakeholders

Full Description

About the position

We are seeking a highly curious, proactive, and innovative Data Scientist with deep experience in AI/ML, NLP, and Large Language Models (LLMs).

The ideal candidate will excel at blending complex datasets, building predictive and statistical models, and delivering AI-driven solutions that create measurable business impact.

This role will work hands-on with advanced LLMs and modern ML frameworks to design, train, deploy, and optimize AI applications within a real-world operational environment. You will partner closely with business and technical stakeholders to translate data science into clear, actionable strategies.

Responsibilities

• AI/ML Model Development: Design, train, fine-tune, and evaluate machine learning and deep learning models—including LLMs—for predictive analytics and automated decision-making.

• Data Engineering & Feature Development: Collect, clean, and analyze structured and unstructured data; engineer features to improve model accuracy and efficiency.

• NLP & Agent-Based AI Applications: Build LLM-powered solutions using prompt engineering, fine-tuning, inference optimization, and agent-based architectures.

• Business Decision Support: Convert statistical and ML findings into practical insights and recommendations that support strategic decisions.

• End-to-End Deployment (MLOps): Implement, deploy, and monitor ML models using best practices for reliability, scalability, and performance.

• Data Storytelling & Communication: Create dashboards, visualizations, and presentations that clearly communicate insights to non-technical stakeholders.

Requirements

• Hands-on experience with AI/ML, NLP, LLM applications (GPT/BERT/LangChain), predictive modeling, and deep learning.

• Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face).

• Advanced SQL skills and experience integrating data from multiple sources.

• Experience with Snowflake, AWS (SageMaker, S3, Redshift), and automated ML pipelines.

• Strong understanding of version control (Git) and collaborative development.

• Highly curious, innovative, and growth-oriented mindset.

• Ability to drive projects independently from ideation to deployment.

• Strong business acumen with the ability to align technical output to business needs.

• Excellent communication skills with the ability to simplify technical concepts.

Nice-to-haves

• Master’s or Ph.

D. in Computer Science, Data Science, Mathematics, Statistics, Engineering, or another quantitative discipline.

• Experience using BI or model-monitoring tools (Power BI, Dash, Streamlit).

• Familiarity with reinforcement learning or agent-based AI systems.