Cost of Vacancy: Data Scientist
Calculate the cost of a vacant Data Scientist role. Analytics backlog, delayed insights, and model maintenance overhead — see the real numbers based on SHRM benchmarks.
Total Cost (62 days vacant)
$228,237
Cost Breakdown
Four cost layers — all calculated transparently from salary, department, seniority, and team data.
Productivity Loss
$76,091Salary/day × 2.0x (Engineering, Senior) × 62 days
Replacement Cost
$101,250SHRM benchmark: 75% of salary for Senior roles
Ramp-to-Productivity
$22,091New hire at reduced output for 120 days after joining
Team Cascade Cost
Often overlooked2 teammates × 30% extra load + burnout cost after 45 days
Projected Total at Fill Date
$321,509
Assumes 60 more days to hire (industry avg for this role type)
Fill 2 Weeks Faster
Save $17,182
Every 14 days saved = $17,182 back in your business
Secondary Turnover Risk
At 62 days with 2 teammates absorbing extra work, this vacancy carries elevated secondary turnover risk. One additional departure would add an estimated $35,438 to your total cost (based on 35% probability × replacement cost).
Why This Role Costs So Much
Data Scientist vacancies are acutely felt in any data-driven organization. Analytics requests back up, model retraining lags, and business decisions get made without the insights they rely on. With a 60-day average time-to-fill in data roles — and a 120-day ramp to full productivity — the effective gap is over 6 months. Meanwhile, two senior data teammates absorbing extra load are approaching burnout threshold.
- Analytics request backlogs grow 3–5x when a DS role is vacant
- Model drift and retraining gaps can degrade prediction quality during vacancy
- Data Science ramp is 120+ days due to domain context and tooling familiarity
- Secondary turnover risk is elevated at 62 days with 2 teammates absorbing extra load
Calculation Assumptions
Benchmarks: SHRM 2025 Recruiting Benchmarking Report
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