Jun Ren Email & Phone Number
@biogen.com
2 phones found area 781
LinkedIn matched
Who is Jun Ren? Overview
A concise factual answer block for searchers comparing this professional profile.
Jun Ren is listed as Associate Director, Data Science, Drug Safety and Pharmacovigilance at Biogen, a company with 7604 employees, based in Raleigh-Durham-Chapel Hill Area, United States, United States. AeroLeads shows a work email signal at biogen.com, phone signal with area code 781, and a matched LinkedIn profile for Jun Ren.
Jun Ren previously worked as Principal Data Scientist, Drug Safety & Pharmacovigilance at Biogen and Senior Data Scientist, Manufacturing at Biogen. Jun Ren holds Doctor Of Philosophy (Ph.D.), Applied Mathematics from Texas A&M University.
Email format at Biogen
This section adds company-level context without repeating Jun Ren's masked contact details.
AeroLeads found 1 current-domain work email signal for Jun Ren. Compare company email patterns before reaching out.
About Jun Ren
• Solid background in machine learning and deep learning.• Computational intelligence for predictive modeling, drug safety analytics.• Extensive hands‑on experience in manufacturing process data, real world evidence/data.• Passionate about automated data science solutions through web-based apps.
Listed skills include Python, R, Matlab, Sas, and 10 others.
Jun Ren's current company
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Jun Ren work experience
A career timeline built from the work history available for this profile.
Principal Data Scientist, Drug Safety & Pharmacovigilance
Current
Senior Data Scientist, Manufacturing
Data Scientist, Manufacturing
Analytics & Applied Stats Researcher
Research Assistant
Colleagues at Biogen
Other employees you can reach at biogen.com. View company contacts for 7604 employees →
Deepika Gundimeda
Colleague at BiogenHyderabad, Telangana, India, India
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MF
Marta Fernández Silva
Colleague at BiogenAarburg, Aargau, Switzerland, Switzerland
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DM
David Mckinley
Colleague at BiogenDewitt, Michigan, United States, United States
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MP
Marc Perahia
Colleague at BiogenGreater Rouen Metropolitan Area, France
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GC
Giorgia Chiricò
Colleague at BiogenLuterbach, Solothurn, Switzerland, Switzerland
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AY
Anton Yevelev
Colleague at BiogenDurham, North Carolina, United States, United States
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KC
Kristina Callen Karassik
Colleague at BiogenDuxbury, Massachusetts, United States, United States
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LC
Lindsay Carlesi
Colleague at BiogenDurham, North Carolina, United States, United States
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AS
Alan Suarez
Colleague at BiogenMexico, Mexico
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GZ
Guanghui Zhao
Colleague at BiogenHuangpu District, Shanghai, China, China
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Jun Ren education
Doctor Of Philosophy (Ph.D.), Applied Mathematics
Master’S Degree, Computational Mathematics
Bachelor’S Degree, Information And Computing Science
Frequently asked questions about Jun Ren
Quick answers generated from the profile data available on this page.
What company does Jun Ren work for?
Jun Ren works for Biogen.
What is Jun Ren's role at Biogen?
Jun Ren is listed as Associate Director, Data Science, Drug Safety and Pharmacovigilance at Biogen.
What is Jun Ren's email address?
AeroLeads has found 1 work email signal at @biogen.com for Jun Ren at Biogen.
What is Jun Ren's phone number?
AeroLeads has found 2 phone signal(s) with area code 781 for Jun Ren at Biogen.
Where is Jun Ren based?
Jun Ren is based in Raleigh-Durham-Chapel Hill Area, United States, United States while working with Biogen.
What companies has Jun Ren worked for?
Jun Ren has worked for Biogen and Texas A&M University.
Who are Jun Ren's colleagues at Biogen?
Jun Ren's colleagues at Biogen include Deepika Gundimeda, Marta Fernández Silva, David Mckinley, Marc Perahia, and Giorgia Chiricò.
How can I contact Jun Ren?
You can use AeroLeads to view verified contact signals for Jun Ren at Biogen, including work email, phone, and LinkedIn data when available.
What schools did Jun Ren attend?
Jun Ren holds Doctor Of Philosophy (Ph.D.), Applied Mathematics from Texas A&M University.
What skills is Jun Ren known for?
Jun Ren is listed with skills including Python, R, Matlab, Sas, C++, Fortran, Machine Learning, and Statistical Modeling.
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