Peloton's workforce data shows contraction across the indicators we'd typically use to distinguish a turnaround in motion from a continued decline.
Headline numbers. 2,875 employees (-9% YoY), 20% attrition, 292 hires against 51 open jobs (1.8% open-jobs rate). At this open-jobs rate, hiring is running close to replacement pace.
Top-5 growing skills are all negative: - MATLAB: -3% - Market Research: -5% - REST APIs: -5% - Engineering: -5% - Radio Production: -6%
All-negative top-5 is uncommon in our dataset; most companies, including those in restructuring, register positive growth on at least one or two skills in the top five.
Talent flow (12mo). Captured outflows: Meta (8), Uber (4), DoorDash (4), Duolingo (3), NYT (3). Captured inflows: Spotify (3), Grubhub (3), LifeLabs Learning (2). Outflow destinations skew larger by headcount and brand profile than inflow destinations on this captured set.
Talent Moat Score: 36/100. TMS is a 100-point composite weighting 5 workforce dimensions equally (20 pts each): Acquisition (net inflow per 1,000 employees), Retention (attrition rate), Skills momentum (top-5 skill growth average), Hiring intent (open jobs as % of headcount), and Pedigree (elite-school concentration). Each sub-score is benchmarked against the Lumen dataset.
Peloton sits near the bottom of the Lumen dataset. Above: Crocs 54, Fossil 46, McKinsey 44, Microsoft 41, Broadcom 41, Target 40. Below: Intel 29. Peloton's 36 reflects elevated attrition (20%), contracting headcount (-9% YoY), all-negative top-5 skill growth, and a 1.8% open-jobs rate.
Peloton Workforce Snapshot
2,875
Employees
-9% YoY
20%
Attrition
vs. Crocs 12%, Skechers 14%, Shopify 11%, Airbnb 7%
292
Hires
12-month captured hires
51
Open Jobs
1.8% open-jobs rate
-4.8%
Top-5 skill growth (avg)
All five skills negative
36/100
Talent Moat Score
Lower band of our consumer cohort
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Analyst
Walk me through the skill trajectory — where is Peloton investing?
LinkedIn Talent Data Insights
Peloton's top-5 growing skills are all negative — uncommon in our dataset — while the absolute skill inventory shows a data-and-engineering-skewed workforce.
Capability tags below describe how each skill family is most commonly applied inside a consumer hardware-and-content company at Peloton's scale.
- MATLAB — mechanical engineering simulation, motor controls, biomechanics modeling. Engineering tooling for hardware product development. - Market Research — strategic experimentation, customer-segment testing, churn-driver analysis. - REST APIs — digital integrations, partnerships, B2B platform connections. - Engineering — general engineering capacity. The 5% YoY contraction is directionally consistent with the headline -9% headcount. - Radio Production — audio engineering and live production capabilities — the operational base behind the instructor-led class output.
Note that the same employee typically holds multiple skill tags so these counts overlap. The inventory is data-and-engineering-heavy — typical of a digital subscription business with significant analytics and product engineering investment historically.
Pattern across the two views. Peloton's existing skill base is data and engineering-oriented (the inventory), but those capabilities are not being expanded — every top-5 growing skill is negative. The workforce is being maintained on its existing skill mix while contracting overall.
Peloton — Top-5 Skills by YoY Change (all negative)
Skill
YoY Growth
Capability typically supported
MATLAB
-3%
Hardware engineering simulation
Market Research
-5%
Strategic experimentation
REST APIs
-5%
Digital integrations / B2B
Engineering
-5%
General product capability
Radio Production
-6%
Live class production
Peloton — Skill Inventory (top 5 by absolute headcount)
Headline totals (LinkedIn, last 12 months): 308 hires, 603 departures, -295 net change.
The captured outflow set sits in larger consumer subscription, marketplace, and media employers, generally paying at the upper end of NYC / Bay Area technical compensation. The captured inflow set is smaller in scale.
Multi-window context. - Meta is the largest single counterparty: 18 departures / 5 hires (24mo), 8 / ~3 (12mo). Persistent net outflow. - Spotify is the largest single inflow source: 5 hires / 1 departure (24mo). The only Big-Tech destination registering a net positive at Peloton. - DoorDash and hims & hers show 8 departures / 0 hires (24mo) — concentrated outflows with no reciprocal inflow.
Outflow vs. inflow on the captured set is roughly 1.8x by volume in the 12-month window (22 outflow vs. 12 inflow across the named top-5s); the asymmetry persists at the 24mo window. Outflow employers skew larger by headcount and external brand profile than inflow employers (Spotify is the notable exception on the inflow side).
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Analyst
How does workforce churn risk look — attrition vs. peers and the Open-to-Work signal?
LinkedIn Talent Data Insights
Two churn-risk lenses: attrition rate against a curated sector cohort, and the LinkedIn Recruiter Open-to-Work signal across reliable role keywords.
Attrition (vs. 19-company sector cohort). Peloton's attrition rate is 20%. The cohort median is 12% and the cohort range is 4–28%. Peloton ranks 17 of 20 on retention (1 = best). The cohort is curated for sector and competitive-talent-market relevance, not just headcount band.
Attrition rate — Peloton vs. sector cohort (lower is better; Peloton highlighted)
Costco Wholesale
4
Kroger
5
Deckers Brands
6
Procter & Gamble
7
Airbnb
7
The Home Depot
9
Walmart
10
Shopify
11
Roku
11
Crocs, Inc.
12
Inspire Brands
12
Target
13
Skechers
14
HubSpot
15
Tubi
15
Canada Goose
18
Peloton
20
Klaviyo
21
Netflix
24
HEYDUDE
28
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LinkedIn Talent Data Insights
Open-to-Work (LinkedIn Recruiter, April 30 2026 data). 1,200 of 2,875 Peloton employees on LinkedIn (42%) are flagged Open-to-Work. 374 (13%) are flagged 'active talent' (actively job-searching).
Peloton's 42% OTW ranks #2 of 9 in the Lumen Apr 30 dataset (range 23–52%; median 37%). See the cohort comparison below.
Peloton Open-to-Work Aggregate (LinkedIn Recruiter, April 30 2026 data)
2,875
Employees on LinkedIn
Total Peloton captured profiles
1,200
Open to Work
42% of captured profiles
374
Active talent
13% — actively job-searching
11
Rediscovered candidates
Engaged with recruiters previously
Peloton Open-to-Work by Skill (LinkedIn Recruiter, April 30 2026 data)
Skill
Captured
Open to Work
% OTW
Active talent
% Active
Software Development
751
295
39%
140
19%
Machine Learning
148
73
49%
40
27%
Sales
922
465
50%
162
18%
Marketing
916
446
49%
178
19%
Operations Management
791
420
53%
164
21%
Financial Analysis
303
138
46%
73
24%
Product Management
752
384
51%
151
20%
Customer Service
1,000
566
57%
186
19%
OTW rate vs Lumen dataset — Apr 30 2026 pull (9 companies, ranked high → low)
Establishment Labs
52%
Peloton
42%
Fox Factory
42%
Crocs
38%
Rivian
37%
Fossil
33%
Roku
31%
Databricks
24%
Snowflake
23%
OTW + active-talent across the Lumen Apr 30 pull
Company
Industry
% OTW
% Active
Establishment Labs
Medical device (small-cap)
52%
14%
**Peloton**
Consumer subscription
42%
13%
Fox Factory
Specialty manufacturer
42%
5%
Crocs
Footwear
38%
9%
Rivian
EV
37%
11%
Fossil
Accessories
33%
9%
Roku
Streaming
31%
12%
Databricks
Data infrastructure
24%
8%
Snowflake
Data infrastructure
23%
13%
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Analyst
Is the B2B pivot visible in the workforce data?
LinkedIn Talent Data Insights
The workforce data does not yet show the build typically associated with a B2B pivot at scale.
What the build typically looks like in workforce data. When a consumer company expands materially into B2B, common workforce patterns include: enterprise sales hires (frequently from Salesforce, Workday, ServiceNow), customer success managers from enterprise SaaS, partnerships and channel managers, and integration engineers building API platforms (SSO, audit logging, admin consoles, multi-seat licensing).
What Peloton's data shows. Headcount by function: Operations 604 (21%), Engineering 518 (18%), Sales 230 (8%), IT 230 (8%), Media & Communications 144 (5%). As a benchmark, consumer subscription companies with material B2B revenue typically run sales between 15-25% of headcount. Reaching 15% from Peloton's current 230-person Sales base would require ~200 additional sales hires; reaching 25% would require ~490.
Open jobs context. Total open jobs across all functions is 51. Even if every open role were Sales, the gap to a 15% Sales-share would still require ~200 additional hires beyond what is currently posted. (Function-level breakdown of open jobs is not available in the captured data.)
REST API skill trajectory. B2B integrations rely heavily on API engineering. Peloton's REST API skill rate is -5% YoY rather than growing.
What's consistent with the data. A small B2B pilot or partnerships motion is consistent with current workforce numbers. A workforce-scale B2B build is not.
Leading indicators to watch. If the B2B build accelerates, we'd expect to see (a) open jobs in Sales and Customer Success expand over the next 2-4 quarters, and (b) hires from enterprise SaaS companies appear in the captured inflows.
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Analyst
How does the NYC geography show up in the workforce data?
LinkedIn Talent Data Insights
Peloton's headcount distribution and recruiting funnel both anchor in NYC.
Top headcount locations (of 2,875 total employees): - New York City Metropolitan Area: 1,152 (40%) - Dallas-Fort Worth Metroplex: 251 (9%) - London Area, UK: 180 (6%) - Los Angeles Metropolitan Area: 101 (4%) - San Francisco Bay Area: 96 (3%) - Greater Seattle Area: 93 (3%) - Taipei-Keelung Metropolitan Area: 50 (2%)
Roughly 40% of the workforce sits in NYC, with secondary clusters in Dallas-Fort Worth, London, and West-Coast US tech markets.
Top schools (alumni count): NYU (36), Rutgers (28), Georgia Tech (27), Penn State (22), Northeastern (21). The recruiting funnel is East Coast-weighted, with NYU as the largest single source. The school list overlaps with the recruiting funnels of larger NYC technical employers (Meta NY, Google NY, JPMorgan, Goldman tech).
Captured outflow geography in context. The largest captured outflow employers — Meta (8), Uber (4), DoorDash (4) — operate at scale in the same NYC labor market for product, engineering, and analytical roles.
What the data does and doesn't show. What it shows: a workforce concentrated in NYC, an East Coast-weighted school funnel, and senior outflow into larger consumer-tech employers in the same market. What it doesn't show in this view: role-level compensation deltas, the share of attrition attributable to comp gap vs. other factors, or the YoY direction of the Dallas / London / Bay Area satellite locations.
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Analyst
Finally, how do these four companies compare on the headline workforce signals?
LinkedIn Talent Data Insights
Four distinct workforce profiles across the four companies. Headline numbers, top-5 skill momentum, and Talent Moat Scores are in the tables below.
One-line read on each company: - Establishment Labs: small-cap medical device in commercial-capacity build (territory + sales-force expansion). Geographic concentration in Costa Rica is the watchpoint. - Fox Factory: healthy specialty manufacturer; the Cosmic Sports outflow cluster (7 departures to a single destination) is the open question. - Fossil: steady-state accessories business with a meaningful Bengaluru operations center; skills clustered around zero. - Peloton: contraction across most workforce indicators; B2B-pivot narrative is not yet visible in the workforce build.
Headline workforce numbers across the four companies
Company
Employees
YoY
Attrition
Hires
Open jobs (rate)
Establishment Labs
933
+2%
12%
122
27 (2.9%)
Fox Factory
2,004
+5%
9%
280
95 (4.7%)
Peloton
2,875
-9%
20%
292
51 (1.8%)
Fossil
5,138
-1%
10%
435
102 (2.0%)
Top-5 skills momentum (average growth across the top-5 fastest-growing skills)
Company
Top-5 avg
Top-5 growing skills
Establishment Labs
+25.6%
Territory Development +30%, Sales Force Development +28%, Sales Processes +24%, Urology +23%, Nursing +23%
Fox Factory
+7.2%
3D Prototyping +10%, Forklift Operation +9%, Business Analysis +7%, Attention to Detail +6%, Operations Management +4%
All workforce data captured from LinkedIn Talent Insights and LinkedIn Recruiter, April 2026.
Captured profiles are LinkedIn-visible employees tagged to a company; this set typically exceeds active headcount because recent ex-employees may still list the company on their profile.
Open-to-Work is LinkedIn's signal where members flag themselves as open to new roles. Reported as a percentage of captured profiles.
Talent Moat Score is a 100-point composite weighting Acquisition, Retention, Skills momentum, Hiring Intent, and Pedigree at 20 points each. Scores are anchored to category benchmarks across the Lumen dataset.