Sidney M. Bell
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Sidney M. Bell Email & Phone Number

Data scientist / computational biologist at Chan Zuckerberg Initiative at Chan Zuckerberg Initiative
Location: San Francisco, California, United States 6 work roles 4 schools
1 work email found @chanzuckerberg.com LinkedIn matched
✓ Verified May 2026 4 data sources Profile completeness 100%

Contact Signals · 1 work email

Work email s****@chanzuckerberg.com
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Current company
Role
Data scientist / computational biologist at Chan Zuckerberg Initiative
Location
San Francisco, California, United States
Company size

Who is Sidney M. Bell? Overview

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Quick answer

Sidney M. Bell is listed as Data scientist / computational biologist at Chan Zuckerberg Initiative at Chan Zuckerberg Initiative, a company with 558 employees, based in San Francisco, California, United States. AeroLeads shows a work email signal at chanzuckerberg.com and a matched LinkedIn profile for Sidney M. Bell.

Sidney M. Bell previously worked as Staff data scientist / computational biologist at Chan Zuckerberg Initiative and Senior Computational Biologist at Chan Zuckerberg Initiative. Sidney M. Bell holds Doctor Of Philosophy (Ph.D.) from University Of Washington.

Company email context

Email format at Chan Zuckerberg Initiative

This section adds company-level context without repeating Sidney M. Bell's masked contact details.

{first_initial}{last}@chanzuckerberg.com
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AeroLeads found 1 current-domain work email signal for Sidney M. Bell. Compare company email patterns before reaching out.

Profile bio

About Sidney M. Bell

Portfolio of projects, code, papers and talks: www.sidneymbell.scienceI design & build software tools which make data more valuable by enabling experts and non-experts alike to explore, visualize and draw conclusions from complex data.

Listed skills include Python, Data Analysis, Bayesian Statistics, Molecular Evolution, and 5 others.

Current workplace

Sidney M. Bell's current company

Company context helps verify the profile and gives searchers a useful next step.

Chan Zuckerberg Initiative
Chan Zuckerberg Initiative
Data scientist / computational biologist at Chan Zuckerberg Initiative
redwood city, california, united states
Employees
558
AeroLeads page
6 roles

Sidney M. Bell work experience

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Team & coworkers

Colleagues at Chan Zuckerberg Initiative

Other employees you can reach at chanzuckerberg.com. View company contacts for 558 employees →

4 education records

Sidney M. Bell education

Education record

International Honors Program
FAQ

Frequently asked questions about Sidney M. Bell

Quick answers generated from the profile data available on this page.

What company does Sidney M. Bell work for?

Sidney M. Bell works for Chan Zuckerberg Initiative.

What is Sidney M. Bell's role at Chan Zuckerberg Initiative?

Sidney M. Bell is listed as Data scientist / computational biologist at Chan Zuckerberg Initiative at Chan Zuckerberg Initiative.

What is Sidney M. Bell's email address?

AeroLeads has found 1 work email signal at @chanzuckerberg.com for Sidney M. Bell at Chan Zuckerberg Initiative.

Where is Sidney M. Bell based?

Sidney M. Bell is based in San Francisco, California, United States while working with Chan Zuckerberg Initiative.

What companies has Sidney M. Bell worked for?

Sidney M. Bell has worked for Chan Zuckerberg Initiative, Fred Hutchinson Cancer Research Center: Bedford Lab, and University Of Utah.

Who are Sidney M. Bell's colleagues at Chan Zuckerberg Initiative?

Sidney M. Bell's colleagues at Chan Zuckerberg Initiative include Lucia Reynoso, Meagan M., Ronald Wu, Kyle Cameron, and Genevieve Erwin Haliburton, Phd.

How can I contact Sidney M. Bell?

You can use AeroLeads to view verified contact signals for Sidney M. Bell at Chan Zuckerberg Initiative, including work email, phone, and LinkedIn data when available.

What schools did Sidney M. Bell attend?

Sidney M. Bell holds Doctor Of Philosophy (Ph.D.) from University Of Washington.

What skills is Sidney M. Bell known for?

Sidney M. Bell is listed with skills including Python, Data Analysis, Bayesian Statistics, Molecular Evolution, Phylogenetics, Statistical Modeling, Machine Learning, and Data Visualization.

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