What are the responsibilities and job description for the Data Scientist Manager (Local to CO) position at Millennium Global Technologies?
Data Scientist Manager
Greenwood village CO
4 days onsite
- T-shaped role combining strong business communication with hands-on data science/analytics execution.
- Own end-to-end delivery—from interpreting vague executive requests to building automated data pipelines.
- Heavy focus on executive presence: clear communication, active listening, and polished presentations.
- Deliver executive-ready insights that answer the “so what” with no additional cleanup needed.
- Act as team lead/mentor, improving junior staff output and introducing better tools/processes.
- Handle rapid-turnaround analytics projects (often within 48–72 hours).
- Build scalable solutions using Python, SQL, and LLM-based automation workflows.
- Navigate technical limitations, bureaucracy, and shifting priorities with creative problem-solving.
- Requires strong ownership mindset, business acumen, and experience with sales/retention/call center domains.
- Bonus: experience with automation/orchestration tools, data architecture, and visual storytelling (dashboards/decks).
Mandatory SkillS
- Strong communication & executive presence (presenting to senior leadership, storytelling)
- End-to-end ownership of analytics projects (problem → solution → delivery)
- SQL proficiency (core data querying skill)
- Python proficiency (data analysis, automation, workflows)
- Experience with LLMs / prompt engineering (practical usage understanding limitations)
- Business acumen (answering “so what,” aligning insights to decisions)
- Rapid delivery mindset (working in tight 48–72 hour timelines)
- Problem-solving in constrained environments (workarounds, dealing with red tape)
- Leadership/mentorship experience (guiding junior team members)
- Domain experience in sales, retention, or call center operations
- High accountability & ownership mindset
Secondary / Bonus SkillS
- Automation & orchestration tools (schedulers, pipelines)
- Advanced workflow automation using LLMs
- Data engineering / architecture fundamentals
- Dashboarding & visual storytelling (clean, executive-ready outputs)
- Design skills / strong presentation aesthetics (deck-building, UX mindset)