Summary:
Our client is seeking to add a Senior Data Scientist to their growing team. This position will involve applying advanced analytics to extract actionable insights from complex datasets, facilitating data-driven decision-making across the organization. The Resource will design and implement predictive models, optimizing business processes through the development of machine learning algorithms. The focus is on delivering measurable outcomes, enhancing productivity, and improving resource allocation. The lasting impact of these contributions will be the integration of data-driven decision-making into the organizational framework, positioning our client at the forefront of innovation in the industry.
Languages/Tools:
- Strong Python (3–5 years minimum).
- Databricks (core platform).
Machine Learning & Modeling:
- End-to-end ML lifecycle: from data exploration to model production.
- No specific library required (Prophet, sklearn, Nixtla, etc. all fine).
- Must be capable of customer-level modeling, forecasting, and segmentation.
Environment:
- Supported by Data Engineering and ML Ops teams.
- Tech stack is straightforward; data structure is nuanced – requires analytical depth and adaptability.
Ideal Candidate Profile:
- Self-starter, comfortable working independently and taking initiative.
- Able to interpret direction and run with tasks.
- Should be comfortable learning new data quickly and contributing in ambiguous environments.
Work Location & Schedule:
- Contractors: Fully remote is acceptable.
- Full-time employees: Expected in-office 3 days/week.
- Anchor days: Tuesday & Wednesday. Flexibility to choose the 3rd in-office day.
- Location flexibility: No strict preference, but it’s a plus if candidates are near: Chicago, IL, Quincy, MA, Salisbury, NC, Greenville, SC, Scarborough, ME, Carlisle, PA, Hanover, MD
