Intern Data Scientist Machine Learning Jobs in Providence, RI

Job Title: Principal Data Scientist, Digital Innovation and Predictive Formulations

Primary Location: in either office: Chicago, IL or Bridgewater, NJ Position

Must Be Citizen or Green Card

A Principal Data Scientist, Digital Innovation and Predictive Formulations to lead the technical strategy, architecture, and execution of advanced data science capabilities for a global food and ingredient innovation organization.

This principal-level professional will design and scale an adaptive data lakehouse and analytical framework that transforms complex scientific and formulation data into actionable insights. The individual will help food scientists and product formulators use data to improve ingredient selection, guide experimentation, develop predictive formulations, and accelerate customer-focused product innovation.

This is a highly visible, hands-on technical leadership role for someone who can establish a long-term data science vision, build production-ready machine learning capabilities, advise business and technical leaders, and mentor other data scientists. The Principal Data Scientist reports to the Director of Digital Innovation.

What You'll Do Lead the design and implementation of a robust, scalable data framework that can evolve with the organization's innovation and product-development needs.

Architect and scale a dynamic data lakehouse and democratized analytical layer within the Google Cloud ecosystem.

Create data capabilities that support ingredient selection, predictive formulation, scientific experimentation, and customer-focused product innovation.

Partner with engineering and technical teams to establish scalable machine learning pipelines that can adapt quickly to emerging business and scientific challenges.

Develop, validate, deploy, and continuously improve machine learning models aligned with evolving business needs.

Apply advanced statistical and machine learning techniques to complex, real-world business and product-development challenges.

Translate business and scientific questions into structured analytical problems and data driven solutions.

Identify and prioritize high-value data science and AI use cases in partnership with digital innovation leadership. Demonstrate the measurable business value, insight, and impact delivered by data science initiatives.

Establish the long-term technical vision for predictive modeling, data science, analytics, and supporting data architecture

Serve as a trusted technical advisor to business leaders, scientific teams, data professionals, and other stakeholders.

Communicate complex technical concepts clearly to technical, business, scientific, and nontechnical audiences.

Mentor and develop data scientists while fostering a culture of technical excellence, curiosity, collaboration, and continuous improvement.

Evaluate emerging capabilities, including generative AI, machine learning platforms, and advanced modeling techniques.

Balance multiple opportunities while prioritizing initiatives based on measurable outcomes, business value, and key performance indicators

What You'll Bring

Significant professional experience in predictive modeling, data science, statistical analysis, and advanced analytics.

Demonstrated ability to establish a long-term technical vision and successfully execute that vision through production implementation.

Proven delivery of multiple major data science initiatives that generated measurable value and actionable insight for business stakeholders.

Experience translating ambiguous business or scientific questions into analytical approaches and practical solutions using available data.

Strong experience designing, building, or scaling enterprise data frameworks, analytical environments, or data lakehouse architectures.

Experience developing and deploying scalable machine learning models and production machine learning pipelines.

Strong programming and data scripting skills using Python and SQL .

Advanced knowledge of statistical methods, predictive modeling, machine learning, and analytical experimentation.

Experience with advanced modeling approaches such as Bayesian inference .

Strong understanding of data architecture, analytical layers, model deployment, and the operational requirements needed to move data science solutions into production.

Experience working within a cloud-based data and analytics environment.

A bachelor's degree or advanced degree in data science, statistics, mathematics, computer science, engineering, or another relevant quantitative field.

Principal-level technical leadership skills with the ability to influence strategy without relying solely on formal authority.

Exceptional stakeholder management, collaboration, presentation, and communication skills. Demonstrated ability to mentor technical professionals and support their continued development. A results-oriented approach focused on measurable value, business outcomes, and key performance indicators

Highly Preferred Qualifications

Strong hands-on experience within the Google Cloud ecosystem .

Experience architecting or scaling a Google Cloud data lakehouse and analytical layer .

Background supporting food science, food product development, ingredient solutions, formulation science, chemicals, consumer products, or another scientific research and development environment.

Experience applying data science to ingredient selection, formulation optimization, experimentation, or product innovation.

Familiarity with generative AI, modern machine learning platforms, and emerging advanced modeling techniques.

Experience working with global and cross-functional groups that include data scientists, engineers, business leaders, researchers, formulators, or scientific professionals.

Ideal Candidate Profile

The strongest candidate will combine three capabilities:

Principal-level data science leadership: Someone who has established technical strategy and delivered multiple high-impact data science initiatives from concept through measurable business results.

Data and machine learning architecture: Someone capable of designing a scalable Google Cloud data lakehouse, analytical layer, and production machine learning pipelines rather than focusing only on individual models.

Scientific and business partnership: Someone who can work effectively with scientists, product-development professionals, engineers, and executives while translating complex technical concepts into clear business value