[Remote] Data Engineer II, Translational Data Science at Valo Health

Remote

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Not SpecifiedCompensation

Junior (1 to 2 years)Experience Level

Full TimeJob Type

UnknownVisa

Pharmaceuticals, Biotechnology, Health TechIndustries

Requirements

Candidates should possess a Bachelor’s degree plus 2 years of experience or a recent Master’s degree in computer science, information systems, computational sciences, or a related field, and familiarity with various clinical data types such as EHR/EMR, clinical trials, and claims. Experience with Python and SQL, including proficiency in databases like PostgreSQL or MySQL, is required, along with familiarity with medical coding systems such as ICD9/10, CPT, ATC, LOINC, SNOMED, and UMLS. Experience with data processing workflows, data platforms like Spark and Snowflake, and cloud environments such as AWS or GCP is also necessary.

Responsibilities

The Data Engineer II will contribute to the development of data transformation pipelines and systems to ingest and harmonize data within Valo’s data ecosystems, working closely with data engineers and data scientists. They will support the data source backend for epidemiology and patient machine learning, build visualization and data extraction tools, and adhere to agile development techniques. The role involves learning to provide high-quality data through unit and validation tests, participating in code reviews, and serving as a dynamic and active team member.

Skills

Data Engineering

EHR Data Processing

Data Transformation

Structured and Unstructured Data Handling

Analysis-Ready Data Products

Collaboration with Data Scientists

Epidemiology

Patient Clustering

Biomarker Analysis

Valo Health

Drug discovery using machine learning technology

About Valo Health

Valo Health focuses on drug discovery and development in the biopharmaceutical sector, utilizing advanced technology to create new drugs and therapies. The company employs its proprietary Opal Computational platform, which integrates machine learning, tissue biology, and patient data to streamline the drug discovery process. This platform allows Valo Health to identify potential drug candidates more quickly and accurately than traditional methods. Valo Health differentiates itself from competitors by combining technology with life sciences, fostering a collaborative culture that addresses significant challenges in drug development. The company's goal is to improve health outcomes for patients worldwide by delivering effective solutions through partnerships with pharmaceutical companies and research institutions.

Boston, MassachusettsHeadquarters

2019Year Founded

$474.2MTotal Funding

LATE_VCCompany Stage

AI & Machine Learning, BiotechnologyIndustries

51-200Employees

Risks

Leadership changes may impact Valo's strategic direction and decision-making.

Heavy reliance on Novo Nordisk partnership poses financial risks if expectations aren't met.

Intensifying competition in AI-driven drug discovery could challenge Valo's market position.

Differentiation

Valo Health integrates AI and human-centric data for drug discovery and development.

The Opal Computational Platform offers an end-to-end solution for drug discovery.

Valo's approach combines machine learning, tissue biology, and patient data for precision therapeutics.

Upsides

Valo's partnership with Novo Nordisk could yield up to $4.6 billion in milestone payments.

The growing market for AI-driven drug discovery platforms supports Valo's business model.

Strategic partnerships with pharmaceutical companies enhance Valo's revenue and market reach.

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