Data Analysis, Data Mining, Drug Discovery, Effective communication skills, Machine learning techniques, Science, Teamwork
The Opportunity
The heart of insitro’s strategy is the combination of novel, cutting edge methods in machine learning, biology at scale and drug discovery capabilities that address key bottlenecks in the drug development pipeline. To accomplish that, we are putting together an incredible team of highly talented drug discovery scientists who want to make a difference by bringing meaningful and accessible medicines to patients with significant unmet needs. In this role, you will help build the cheminformatics and drug discovery data engineering capabilities.
Key Responsibilities
You will be joining a growing biotech startup that has long-term stability due to significant funding, but yet is very much in formation. A lot can change in this early and exciting phase, providing many opportunities for significant impact. You will work closely with a very talented team, learn a broad range of skills, and help shape insitro’s culture, strategic direction, and outcomes. Join us, and help make a difference to patients!
About You
Compensation & Benefits at insitro
Our target starting salary for successful US-based applicants for this role is $130,000 - $145,000. To determine starting pay, we consider multiple job-related factors including a candidate’s skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data.
This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies.
In addition, insitro also provides our employees:
insitro is a data-driven drug discovery and development company using machine learning and data at scale to transform the way that drugs are discovered and developed for patients. insitro is developing predictive machine learning models to discover underlying biologic state based on human cohort data and in-house generated cellular data at scale. These predictive models can be brought to bear on key bottlenecks in pharmaceutical R&D.
South San Francisco, CA, USA
2-4 year
South San Francisco, CA, USA
4-6 year
South San Francisco, CA, USA
2-4 year
South San Francisco, CA, USA
4-6 year
South San Francisco, CA, USA
4-6 year
South San Francisco, CA, USA
2-4 year
South San Francisco, CA, USA
0-2 year
South San Francisco, CA, USA
2-4 year
South San Francisco, CA, USA
0-2 year
South San Francisco, CA, USA
6-8 year
South San Francisco, CA, USA
2-4 year
South San Francisco, CA, USA
0-2 year
South San Francisco, CA, USA
0-2 year
South San Francisco, CA, USA
6-8 year
South San Francisco, CA, USA
4-6 year