Data Scientist, AI Engineering

Position: Data Scientist, AI Engineering

Location: Centennial, CO

Duration: Long Term

Job Description:

As a Data Scientist, AI Engineering on the Operational Analytics & Insights team, you'll work in a fast-paced, collaborative environment to develop data-driven solutions to Client's business problems. You'll have the unique opportunity to leverage and work with cutting-edge AI technologies, including real-time transcriptions and other advanced AI applications. You'll be empowered to think of new approaches, use analytical, statistical, and programming skills to analyze and interpret data sets, and apply your AI expertise at scale. This role offers an excellent opportunity to lead projects, drive innovative solutions, and further advance your skills and career with Client, all while making a significant impact on our operations and customer experiences.

WHAT OUR DATA SCIENTISTS ENJOY MOST

• Leveraging knowledge in analytical and statistical algorithms to assist stakeholders in improving their business
• Partnering on the design and implementation of statistical data quality procedures for existing and new data sources
• Communicating complex data science solutions, concepts, and analyses to team members and business leaders
• Presenting data insights & recommendations to key stakeholders
• Establishing links across existing data sources and finding new, interesting data correlations
• Ensuring testing and validation are components of all analytics solutions

You'll work in a dynamic office environment. You'll excel in this role if you are a self-starter who can work independently as well as in a team. If you're comfortable presenting data and findings in front of team members & stakeholders and have excellent problem-solving skills, this could be the role for you.

Required Qualifications

Experience:

• Data analytics experience: 3 years; Programming experience: 2 years

Education:

• Bachelor's degree in computer science, statistics, or operations research, or equivalent combination of education and experience

Skills:

• Strong proficiency in predictive analytics, prescriptive analytics, AI, machine learning, and statistical modeling
• Proficiency in programming languages such as Python and SQL for data analysis and model development.
• Hands-on experience with Large Language Models (LLMs) (finetuning, retraining, and prompt engineering)
• Working with text data including Natural Language Processing (NLP) techniques such as tokenization, lemmatization, sentiment analysis, text classification, topic modeling, and entity recognition
• Hands-on experience with advanced AI techniques such as Retrieval-Augmented Generation (RAG), vector databases, and LLM integration for enhanced information retrieval and generation, GPT, and BERT

Preferred Qualifications:

Experience:

• ML frameworks such as TensorFlow, PyTorch, Scikit-learn, and NLP libraries like spaCy or Hugging Face Transformers

Skills:

• Strong understanding of Machine Learning concepts including supervised and unsupervised learning, model training, evaluation, and deployment

Abilities:

• Develop and demonstrated knowledge of deploying ML models in cloud environments (Azure, AWS, or similar)
• Explain complex AI concepts to non-technical audience