Senior Data Scientist
Typical senior band in MemphisIllustrative pay-band example. Not a live posting — figures derived from BLS OEWS May 2024 medians for this metro.
302 data scientists employed in metro (BLS May 2024) · $97,431 median · 10% below the national median.
The band below shows the 25th–75th percentile range for this occupation in the Memphis metro. Half of Data Scientists earn inside that band.
Source: BLS Occupational Employment & Wage Statistics, May 2024 OEWS estimates. Full Data Scientist salary guide →
The cards below are illustrative pay-band examples — not live postings. Each shows the typical salary range you can expect at that seniority level, derived from BLS OEWS May 2024 medians for this metro. When Jobeezy matches you to a real opening, we auto-apply on your behalf.
Illustrative pay-band example. Not a live posting — figures derived from BLS OEWS May 2024 medians for this metro.
Illustrative pay-band example. Not a live posting — figures derived from BLS OEWS May 2024 medians for this metro.
Illustrative pay-band example. Not a live posting — figures derived from BLS OEWS May 2024 medians for this metro.
Illustrative pay-band example. Not a live posting — figures derived from BLS OEWS May 2024 medians for this metro.
Illustrative pay-band example. Not a live posting — figures derived from BLS OEWS May 2024 medians for this metro.
Expected pay at each step, scaled to Memphis’s median. Your actual offer depends on employer, sub-specialty, and interview performance.
Multipliers calibrated against BLS OEWS May 2024 occupational percentiles for 15-xxxx codes.
Representative large employers for this occupation industry. Jobeezy auto-applies when any qualifying opening posts at these or other employers on Greenhouse, Lever, Workday, Ashby, or iCIMS.
Employers in the Memphis metro typically post Data Scientist roles through one of five applicant tracking systems. Pick the guide that matches where you’re applying:
Pulled from O*NET work-activities and real interview patterns for this occupation. Practice all four with Jobeezy’s InterviewRide drills.
How do you handle class imbalance in a binary classification problem?
Evaluates ML fundamentals: oversampling (SMOTE), undersampling, class weights, threshold tuning, PR-AUC over ROC-AUC.
Describe your process for feature selection when you have 500+ candidate features.
Tests statistical rigor and pragmatism: correlation analysis, importance scores, regularization, domain knowledge.
How would you explain p-values to a non-technical executive?
Communication skill. Avoid jargon: 'How surprising is this result if nothing was actually happening?'
Your model has high training accuracy but poor test accuracy. What do you investigate?
Classic overfitting diagnosis. Data leakage, distribution shift, regularization, simpler model baseline.
Free to start. No resume writing. No cover letters. We handle the search, the filter, and the apply — you just say yes to interviews.
Free on iPhone and Android. You can delete your account in one tap.