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Neuro Data Engineer Jobs (NOW HIRING)

Data Infrastructure Engineer

San Francisco, CA ยท On-site

$140K - $180K/yr

About the Role As a Data Infrastructure Engineer , you will build the backend and hardware ... You will be powering our foundational model training by bridging the gap between physical neuro ...

Data Architect

Bedford, MA ยท On-site

$67 - $86.25/hr

Today, we're expanding our portfolio and pipeline across oncology, neurology and cardiology ... This individual will focus on the Operations side of DevOps and will co-lead the design ...

Data Architect

Bedford, MA ยท On-site

$67 - $86.25/hr

Today, we're expanding our portfolio and pipeline across oncology, neurology and cardiology ... This individual will focus on the Operations side of DevOps and will co-lead the design ...

Position Overview : We are looking for a talented data scientist/algorithm engineer who is ... neurological indications * Analyze data for trends and patterns, and interpret data with a clear ...

Position Overview : We are looking for a talented data scientist/algorithm engineer who is ... neurological indications * Analyze data for trends and patterns, and interpret data with a clear ...

Data Scientist

Sunnyvale, CA ยท On-site

$184K - $210K/yr

Position Overview : We are looking for a talented data scientist/algorithm engineer who is ... neurological indications * Analyze data for trends and patterns, and interpret data with a clear ...

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Showing results 1-20

Neuro Data Engineer information

See salary details

$44.5K

$129.7K

$177.5K

How much do neuro data engineer jobs pay per year?

As of Jun 6, 2026, the average yearly pay for neuro data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Neuro Data Engineer, and why are they important?

To thrive as a Neuro Data Engineer, you need strong expertise in neuroscience, data analysis, and programming skills (often in Python or MATLAB), typically backed by a degree in computer science, neuroscience, or a related field. Familiarity with neuroimaging tools (like fMRI or EEG analysis software), machine learning frameworks, and big data platforms is highly valuable. Excellent problem-solving, collaboration, and communication skills help in translating complex neural data into actionable insights for research or clinical applications. These competencies are crucial for ensuring accurate data handling, effective interdisciplinary teamwork, and advancement in neurotechnology projects.

What are Neuro Data Engineers?

Neuro Data Engineers are specialized professionals who design, develop, and maintain data systems that support neuroscience research and applications. They work at the intersection of data engineering and neuroscience, handling large and complex datasets such as brain imaging, neural recordings, and genetic data. Their responsibilities include building data pipelines, ensuring data quality, and collaborating with neuroscientists to enable efficient analysis and interpretation of neural data. By leveraging advanced technologies and programming skills, Neuro Data Engineers help accelerate discoveries in brain research and related fields.

How do Neuro Data Engineers typically collaborate with neuroscientists and clinical teams in research environments?

Neuro Data Engineers often work closely with neuroscientists and clinical professionals to design data pipelines, manage large-scale neural datasets, and ensure data quality for research studies. Collaboration includes translating scientific requirements into technical solutions, supporting data preprocessing, and developing analytical tools tailored to neuroscience workflows. Regular meetings, code reviews, and interdisciplinary workshops are common, fostering a team environment where technical and scientific expertise are integrated to drive research forward.

What is the difference between Neuro Data Engineer vs Data Scientist?

AspectNeuro Data EngineerData Scientist
Required CredentialsBachelor's or Master's in Neuroscience, Computer Science, or related fields; experience with data engineering toolsBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming and analytics
Work EnvironmentNeuroscience labs, research institutions, healthcare settingsTech companies, research firms, finance, healthcare
Employer & Industry UsageNeuroscience research, neurotechnology companies, healthcare providersTech firms, consulting, research, analytics

Neuro Data Engineers focus on building and maintaining data pipelines for neuroscience data, while Data Scientists analyze data to extract insights. Both roles require strong technical skills, but Neuro Data Engineers emphasize data infrastructure in neuroscience contexts, whereas Data Scientists focus on data analysis and modeling across industries.

Infographic showing various Neuro Data Engineer job openings in the United States as of May 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 100% In-person job distribution, with an average salary of $129,716 per year, or $62.4 per hour.
Associate Director, Data Science - Market Access

Associate Director, Data Science - Market Access

Sanofi EU

Jersey City, NJ โ€ข On-site

$61K - $62K/yr

Full-time

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Job Title: Associate Director, Data Science - Market Access

Location: Cambridge, MA, Morristown, NJ

About the Job

Join the team transforming care for people with immune challenges, rare diseases, cancers, and neurological conditions. In Specialty Care, youโ€™ll help deliver breakthrough treatments that bring hope to patients with some of the highest unmet needs.

Join Sanofi in one of our US Market Access Shared Services functions and you can play a vital part in the performance of our entire business while helping to make an impact on millions around the world. Work collaboratively with matrix partners to manage the strategic attainment of product access and appropriate reimbursement at key customers by participating in and overseeing the negotiation process of financial terms, as well as documented terms and conditions, for assigned customers.

About Sanofi:
Weโ€™re an R&D-driven, AI-powered biopharma company committed to improving peopleโ€™s lives and delivering compelling growth. Our deep understanding of the immune system โ€“ and innovative pipeline โ€“ enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve peopleโ€™s lives.

Main Responsibilities:

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As the Associate Director of Data Science, you will lead the development and delivery of advanced analytics solutions to support market access and pricing decisions. You will perform sophisticated analyses on patient longitudinal data, develop interactive dashboards and reports, and translate complex data into actionable insights for stakeholders. Your role will involve partnering with various departments to support strategic initiatives and leveraging analytics capabilities to enhance data-driven decision-making. Core responsibilities of the role are as follows:

  • Design, develop, and deploy predictive models and analytical solutions using Dagster/Airflow and DBT workflows to drive data-informed market access and pricing decisions. Hands on experience with R and/or Python is required.

  • Architect and maintain scalable datasets that integrate with existing data engineering infrastructure and support cross-functional analytical needs

  • Create interactive dashboards and reports using business intelligence tools that translate complex data into actionable insights for stakeholders

  • Perform advanced statistical analysis on patient longitudinal data and large customer datasets to identify trends, patterns, and strategic opportunities

  • Develop and implement machine learning algorithms to enhance forecasting capabilities and predictive analytics across market access functions

  • Collaborate closely with the data engineering team, SQL developers, and analytics product management to ensure data quality, pipeline efficiency, and business alignment

  • Serve as the technical bridge between data engineering infrastructure and business-facing analytics, ensuring seamless integration of analytical solutions

  • Partner cross-functionally with Pricing, Contract Development, Value and Access, Account Management, Finance, Forecasting, and Data Management teams to drive strategic initiatives

  • Communicate complex analytical findings through compelling data narratives and visualizations tailored to diverse audiences

  • Continuously evaluate and implement emerging methodologies and technologies in data science to advance the team's predictive capabilities

About You

Experience:

  • 5+ years of experience in data science or advanced analytics within Pharmaceutical or Payer organizations

    5+ years of hands-on experience building and deploying predictive models and machine learning solutions on large-scale datasets

  • Demonstrated experience working with workflow orchestration tools (Dagster, Airflow, or similar) to productionize analytical models

  • Proven track record of translating business problems into data science solutions that drive measurable outcomes

  • Experience collaborating with data engineering teams and contributing to data pipeline development

Technical Skills:

  • Advanced proficiency in Python or R for statistical modeling, machine learning, and data analysis

  • Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch, XGBoost, etc.) and predictive modeling techniques

  • Hands-on experience with workflow orchestration platforms (Dagster, Airflow, Prefect, or similar)

  • Proficiency in SQL for complex data manipulation and working with relational databases

  • Expertise in data visualization tools (Tableau, Power BI, or similar) and creating executive-level dashboards

    Experience with cloud platforms (Kubernetes) and modern data stack technologies

  • Strong foundation in statistical methods, experimental design, and A/B testing

  • Understanding of MLOps principles and model deployment best practices

Domain Knowledge:

  • Deep understanding of pharmaceutical market access, pricing strategies, and reimbursement dynamics

  • Experience analyzing longitudinal patient data, claims data, and formulary datasets

  • Working knowledge of the US healthcare system, payer landscape, and regulatory environment

  • Familiarity with healthcare data standards (e.g., NDC, HCPCS, ICD codes, IQVIA)

    ย 

Soft Skills:

  • Exceptional problem-solving abilities with a structured, hypothesis-driven approach

  • Strong communication skills with ability to translate complex technical concepts for non-technical stakeholders

  • Proven ability to manage multiple analytical projects simultaneously and meet deadlines

  • Collaborative mindset with experience working across data engineering, product management, and business teams

  • Detail-oriented with strong organizational and project management capabilities

  • Self-directed learner who stays current with emerging data science methodologies and technologies

  • Ability to mentor and provide technical guidance to developers and junior analysts

    ย 

    ย 

Education:

  • BA or BS Degree

  • Advanced Degree

Why Choose Us?ย 

  • Bring the miracles of science to life alongside a supportive, future-focused team.ย 

  • Discover endless opportunities to grow your talent and drive your career, whether itโ€™s through a promotion or a lateral move, at home or internationally.ย 

  • Enjoy a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact.ย 

  • Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high-quality healthcare, prevention and wellness programs, and at least 14 weeksโ€™ gender-neutral parental leave.ย 

Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.

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All compensation will be determined commensurate with demonstrated experience. Employees may be eligible to participate in Company employee benefit programs, and additional benefits information can be found here.