TARA Biosystems, Inc. is rapidly growing life science company developing physiologically relevant ”heart‐on‐a‐chip” tissue models and proprietary cardiac data analytics for drug discovery, modeling disease and development applications. We operate in a fast‐paced environment where you will have the opportunity to contribute to all facets of the business, from reinforcing TARA’s solid scientific reputation to cementing a lasting company culture based on innovation and mutual respect. TARA is seeking a high performing and enthusiastic individual who can quickly integrate into our team and make an impact on day one!
As a key member of our growing scientific team, you will be part of our R&D group and play a vital role in building a thriving TARA data ecosystem. As a Data Scientist, you will work with other TARA scientists and engineers to structure, integrate and analyze data of diverse types and sources. You will become fluent in the data generated with our engineered tissue models, so prior experience in a laboratory setting using molecular and cellular techniques (especially microscopy) is a valuable asset for this position. You will have the opportunity to work across multiple data science domains. For example, you will structure TARA data in readily accessible formats and repositories, code algorithms and applications, build statistical models, and prepare quantitative information to internal and external stakeholders. Machine learning is an important part of this role, and applications include mining for predictive features influencing experimental outcomes and clustering biological responses to treatments, genetic alterations and other experimental/metadata inputs. You will play a key role in expanding our ML and AI efforts to maximize our ability to predict clinically-relevant outcomes using our tissue models.
ESSENTIAL DUTIES AND RESPONSIBILITIES
- Write code to accomplish diverse data tasks (most commonly in Python and MATLAB).
- Create and refine algorithms for analysis of TARA data including approaches for image and spectral analyses.
- Structure TARA data for facile retrieval, analysis, and accessibility for applications including machine learning.
- Deploy machine learning across the entire domain of TARA data. Establish scalable, efficient and automated processes for large scale data analyses and model development.
- Perform statistical analyses of TARA data, including experimental design and interpretation as well as exploratory and confirmatory analyses.
- MS/PhD in a quantitative/scientific/engineering field like computer science, computational biology, data science, math, statistics, bioengineering, bioinformatics.
- Demonstrated experience with Machine Learning approaches including use of tools like Apache Spark, Tensorflow, Amazon Sagemaker. Experience with cloud deployment is a plus.
- Solid understanding of fundamental statistical principles including hypothesis testing and underlying assumptions, distributions, outlier detection, probabilities, etc.
- Working experience with databases (esp. relational, graph and key-value pair), SQL queries, and complementary tools like regular expression.
- Productive experience with program management: able to coordinate projects with clear goals, deliverables and timelines using most effective and appropriate methodologies.
- Please highlight any prior laboratory experience in cellular and molecular biology, bioengineering or related areas with your application.
- Prior experience in biotech/biopharma/pharma is preferred but not required.
Please note this position is based at our labs and offices in New York City. You will need to be based in the New York City area ultimately as well.
COMPENSATION AND BENEFITS
In addition to a competitive compensation package that includes stock options and bonus eligibility, TARA promotes work/life balance and the overall health and wellbeing of its employees through an attractive, comprehensive benefits program.
Please submit a cover letter and résumé to email@example.com.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.