Data Scientist
Listed on 2026-01-12
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IT/Tech
Data Scientist, AI Engineer, Data Analyst, Machine Learning/ ML Engineer
Position: Senior Data Scientist (Lean Six Sigma Black Belt or Six Sigma Black Belt (Active certification mandatory).
Location: Denver, CO
Duration: 6 months
Interview: In Person interview required
Job SummaryData Scientist (Lean Six Sigma Black Belt or Six Sigma Black Belt (Active certification mandatory).
Note- Should have experience Operational Analytics & Insight (OAI) team.
- Should have experience within Operational Analytics & AI.
The Senior Data Scientist will serve as a technical lead in the development of advanced analytical solutions. This role uniquely combines Generative AI innovation with Six Sigma operational rigor to drive measurable improvements across Spectrums network and customer ecosystems. You will not only build models but also optimize the processes they inhabit to ensure maximum ROI and statistical stability.
Key Responsibilities- Generative AI Strategy:
Lead the research and implementation of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to automate complex business workflows and enhance internal knowledge management systems. - (Black Belt):
Apply DMAIC methodology to the data science lifecycle. Identify root causes of operational inefficiencies and deploy AI solutions to mitigate them. - Advanced Modeling:
Build validate and deploy high-impact predictive models (Churn CLV Propensity) using Python PyTorch and Scikit-learn. - Process Optimization:
Utilize Black Belt principles to reduce waste in data pipelines improving model training and inference efficiency within Databricks/AWS. - Stakeholder Storytelling:
Act as a bridge between technical AI labs and executive leadership translating complex neural network outputs into Six Sigma-validated business cases.
- GenAI Stack:
Experience with Lang Chain, Llama Index, Vector Databases (Pinecone/Milvus) and fine-tuning open-source models. - Data Engineering:
Expert-level SQL and PySpark for grooming large-scale datasets. - Statistical Control:
Deep understanding of Design of Experiments (DoE), hypothesis testing and Statistical Process Control to monitor model drift and performance. - MLOps:
Proficiency in versioning and deploying models in cloud environments (Azure/AWS).
Masters or PhD in a quantitative field (Statistics, CS, Engineering).
CertificationLean Six Sigma Black Belt or Six Sigma Black Belt (Active certification mandatory).
ExperienceOverall 12 plus years of experience in a data-driven environment with a proven track record of leading AI initiatives.
Key Skills- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
Employment Type: Full Time
Experience: Years
Vacancy: 1
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