Principal Scientific Data Engineer (Remote)

Key Skills

AWS, Continuous Integration & Continuous Delivery - CI/CD, Database, Java Programming, Machine learning techniques, NoSQL, Optimization, Predictive analytics, Python Programming, R Programming, SDLC, SQL

Job Description

Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams rich in diversity. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us.

This role can be fully remote:

When you join BMS, you are joining a diverse, high-achieving team united by a common mission. 

The Informatics and Predictive Sciences (IPS) mission is to Pioneer, Partner and Predict to drive transformative insights for patient benefit. IPS conducts applied computational research in areas that include genomic, structural and molecular informatics, computational and systems biology, patient selection and translational biomarker research, and broader fields including knowledge science, epidemiology and machine learning—across the full lifecycle of drug discovery and development and across all therapeutic areas at BMS. We do this in close partnership with scientific and clinical experts in the field, both inside and outside the company.  We perform innovative science to empower key data-driven decisions across a rich pipeline of next-generation medicines. In doing so, our work transforms the lives of patients, as well as our own lives and careers.

Here, you’ll get the chance to grow and thrive through opportunities that are uncommon in scale and scope. You’ll pursue innovative ideas while advancing professionally alongside some of the brightest minds in biopharma.

Bristol Myers Squibb seeks a hardworking individual to contribute to groundbreaking informatics and data management initiatives within Research. This hands-on role interfaces closely with scientists in the Chemistry, Biotherapeutics, and Informatics and Predictive Sciences groups working to identify novel therapies. We are seeking an individual with extensive experience integrating data and building data solutions to make data accessible and relevant for the research community.

Responsibilities include, but are not limited to, the following:

• Innovate and advise on the latest technologies and standard methodologies in Data Engineering.
• Collaborate with colleagues across Informatics and Predictive Sciences to make a wide variety of data, from raw to scientific insights, readily available to researchers.
• Design and develop infrastructure and processes to load public and proprietary data from multiple source systems leveraging a mix of custom software and database development, open-source tools, and cloud-based services.
• Work with multi-functional teams to design and build cloud-based, integrated data platforms to facilitate the identification of novel therapeutic compounds.

• Collaborate with analysts to apply solutions for integration and delivery of complex biologic data to a wide variety of predictive modeling approaches.
• Collaborate with the project manager, solution architect, infrastructure team, and external vendors as needed to support successful delivery of technical solutions.

Basic Qualifications:

• Bachelor's Degree 8+ years of academic / industry experience in an engineering or biology field
• or Master's Degree 6+ years of academic / industry experience in an engineering or biology field
• or PhD 4+ years of academic / industry experience in an engineering or biology field

Preferred Qualifications:

• Minimum 3 years experience in Pharmaceutical, Biotech or Healthcare Industries
• Demonstrated proficiency in processing, analyzing, and constructing complex data capture, management, and dissemination solutions for public or proprietary biological patient and assay datasets including transcriptomic, proteomic, and/or small molecule datasets.
• Demonstrated proficiency with predictive modeling approaches, and/or preparing data for predictive modeling.
• Demonstrated proficiency with current software engineering methodologies, such as Agile SDLC approaches, distributed source code control, project management, issue tracking, and CI/CD tools and processes.
• Excellent skills in an object-oriented programming language such as Python or Java, and proficiency in SQL and R.
• High degree of proficiency in cloud computing. Preference will be given to candidates with AWS experience.
• Solid understanding of container strategies such as Docker, Fargate, ECS, and ECR.
• Excellent skills and deep knowledge of databases such as Postgres, Elasticsearch, Redshift, and Aurora, including distributed database design, SQL vs. NoSQL, and database optimizations.
• Experience developing web applications in frameworks like Shiny, Vue, React, etc. is a plus.
• Along with programming proficiency, must have a strong capacity for independent thinking and the ability to grasp underlying scientific questions.
• Must have experience leading complex scientific data management and integration initiatives in a research environment.
• Must be effective in a dynamic environment while adapting to changing priorities and have excellent written and verbal communication and presentation skills.
• Must have excellent time management and interpersonal skills.

The starting compensation for this job is a range from $121,000 to $167,200, plus incentive cash and stock opportunities (based on eligibility).