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Associate Data Science R Jobs in New York, NY (NOW HIRING)

Advanced degree in Computer Science, Data Science, Machine Learning, AI, Engineering, Mathematics, Statistics, or a related quantitative field. 1-3 years of experience working with data, analytics ...

Advanced degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Engineering, Mathematics, Statistics, or a related quantitative field. 1-3 years of experience working ...

Data Scientist Associate

Manhattan, NY · On-site

$65K - $65K/yr

As an Associate Data Scientist, you will partner with a sales-focused organization to deliver ... Your work will integrate data science, research, and business domain expertise to inform strategic ...

Data Scientist Associate

Manhattan, NY · On-site

$65K - $65K/yr

As an Associate Data Scientist, you will partner with a sales-focused organization to deliver ... Your work will integrate data science, research, and business domain expertise to inform strategic ...

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How much do associate data science r jobs pay per year?

As of Jun 11, 2026, the average yearly pay for associate data science r in New York, NY is $74,437.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,500.00 and $65,100.00 per year, depending on experience, location, and employer.

Is 40 too late for data science?

Age is not a barrier to becoming a data scientist or an associate data science R. Many professionals transition into data science later in their careers by acquiring relevant skills such as programming in R or Python, understanding statistics, and completing certifications or courses. Employers value skills and experience over age, and continuous learning can help you succeed in the field regardless of when you start.

What can I do with an associate's degree in data science?

An associate's degree in data science prepares individuals for entry-level roles such as data analyst, data technician, or junior data scientist. These positions involve working with data collection, cleaning, basic analysis, and using tools like Excel, SQL, or Python. Additional certifications and hands-on experience can enhance job prospects in this field.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this rule to focus on the most impactful variables or tasks to improve model performance efficiently.

What jobs can I get with R?

With R skills, you can pursue roles such as data analyst, data scientist, statistical programmer, or research analyst. These positions typically require proficiency in data manipulation, statistical modeling, and visualization, often using R packages like ggplot2, dplyr, and caret, and may involve working in industries like finance, healthcare, or technology.
What are the most commonly searched types of Data Science R jobs in New York, NY? The most popular types of Data Science R jobs in New York, NY are:
Infographic showing various Associate Data Science R job openings in New York, NY as of June 2026, with employment types broken down into 75% Full Time, and 25% Part Time. Highlights an 100% In-person job distribution, with an average salary of $74,437 per year, or $35.8 per hour.
Associate Director, Data Science - Market Access

Associate Director, Data Science - Market Access

Sanofi EU

Manhattan, NY

$64K - $65K/yr

Full-time

Posted 9 days ago


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, you’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:
We’re an R&D-driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – 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 people’s lives.

Main Responsibilities:

 

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)

     

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

     

     

Education:

  • BA or BS Degree

  • Advanced Degree

Why Choose Us? 

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

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

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

  • 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 weeks’ gender-neutral parental leave. 

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.