Senior Manager, Materials Science, Japan at Schrödinger

Tokyo, Japan

Schrödinger Logo
Not SpecifiedCompensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Materials Science, Computational ChemistryIndustries

Requirements

  • PhD in molecular simulation of Materials Science, or a related field
  • At least eight years of experience in computational materials science, with three to five years in a leadership role
  • Business-level English skills for global collaboration and technical communication
  • Molecular dynamics simulation expert with proven experience in polymer materials and complex material systems
  • Technical leader who understands both underlying scientific methodology and big-picture business implications
  • Proven people manager who excels at developing talent and building high-performing teams
  • Enthusiastic traveler who enjoys visiting customer sites across Japan
  • Experience in customer-facing roles within the scientific software industry (preferred)
  • Experience with business development, sales support, or customer success in B2B technical environments (preferred)

Responsibilities

  • Serve as a core member of the Japan Leadership Team (JLT), contributing to the strategic direction, organizational development, and overall success of Schrödinger KK
  • Collaborate with Sales to develop and execute ambitious strategic business plans
  • Provide expert scientific guidance on complex materials design challenges, including executive presentations, strategic account management, and resolution of challenging technical implementations
  • Collaborate cross-functionally with Sales, Product Management, Marketing, and global Applications Science teams to drive revenue growth, communicate customer needs, and align regional strategies with company objectives
  • Establish scientific thought leadership in computational materials science through research initiatives, high-impact publications, conference presentations, and representation of Schrödinger at major industry events
  • Manage all technical operations including troubleshooting of scientific workflows, oversight of contract research services, and guidance of customer application strategies to ensure optimal use of Schrödinger's materials science platform
  • Oversee pre- and postsales software support operations
  • Manage key customer relationships
  • Guide the strategic development of Materials Science offerings in Japan

Skills

Key technologies and capabilities for this role

Molecular Dynamics SimulationPolymer MaterialsComputational Materials ScienceMaterials DesignTeam ManagementStrategic Account ManagementExecutive PresentationsResearch PublicationsConference PresentationsPre-sales SupportPost-sales SupportCustomer Relationship Management

Questions & Answers

Common questions about this position

What is the compensation for this Senior Manager role?

Schrödinger offers a highly competitive compensation package including base salary, performance-based bonuses, and equity participation.

Is this position remote or based in a specific location?

This information is not specified in the job description.

What qualifications are required for this role?

Candidates need a PhD in molecular simulation of Materials Science or a related field, at least eight years of experience in computational materials science with three to five years in a leadership role, and business-level English skills.

What benefits does Schrödinger offer?

Benefits include comprehensive packages with mutual-aid retirement plans and over four weeks of paid time off.

What makes a strong candidate for this position?

Ideal candidates are molecular dynamics simulation experts with experience in polymer materials, proven technical leaders who understand science and business, experienced people managers, and enthusiastic travelers comfortable with customer visits across Japan; preferred experience includes customer-facing roles in scientific software and business development.

Schrödinger

Computational platform for biopharmaceutical research

About Schrödinger

Schrödinger provides a computational platform that aids in the research efforts of biopharmaceutical companies, academic institutions, and government laboratories around the world. Their platform offers advanced computational tools that help in drug discovery and development across various therapeutic areas. Schrödinger's products work by using sophisticated algorithms and simulations to predict how different compounds will interact, which can significantly speed up the research process. Unlike many competitors, Schrödinger not only licenses its software but also engages in collaborative research and drug discovery programs, allowing for a more integrated approach to scientific research. The company's goal is to enhance scientific research and development through its platform, ultimately leading to the discovery of new drugs and therapies.

New York City, New YorkHeadquarters
1990Year Founded
$362.7MTotal Funding
IPOCompany Stage
Government & Public Sector, Enterprise Software, BiotechnologyIndustries
501-1,000Employees

Benefits

Health Insurance
Dental Insurance
Vision Insurance
401(k) Company Match
401(k) Retirement Plan
Flexible Work Hours
Remote Work Options
Paid Vacation
Parental Leave

Risks

Recursion and Exscientia merger creates strong AI-driven drug discovery competitor.
Avicenna's independent expansion could lead to competitive tensions with Schrödinger.
High R&D costs may strain resources despite Gates Foundation's $10M grant.

Differentiation

Schrödinger's platform supports diverse clients, including biopharma, academia, and government labs.
The company excels in rapid drug discovery, exemplified by SGR-1505's swift development.
Schrödinger's collaboration with Avicenna enhances medicinal chemistry through machine learning.

Upsides

$19.5M Gates Foundation grant boosts platform for neglected diseases, expanding market reach.
Predictive toxicology tools initiative could lead to safer, efficient drug development.
SGR-1505 discovery showcases ability to reduce drug discovery timelines significantly.

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