Data Scientist

What You'll Do

What the role is about: As a Principal/Staff Data Scientist , you will serve

as a senior individual contributor responsible for defining analytical approaches,

scoping complex data science projects, and delivering high-impact solutions across

multiple industries. You will tackle highly complex and ambiguous problems,

architect end-to-end data science workflows, and provide deep technical guidance

to cross-functional teamswithout direct people management responsibilities.

What impact this role has: Your expertise will shape the technical direction of data

science initiatives, influence solution design across teams, and help internal and

external stakeholders make well-informed decisions. By leveraging advanced

modeling, statistical rigor, and deep domain insight, you will ensure th

delivers scalable, high-quality analytical solutions that drive measurable business

value for our clients.

What success might look like: Success in this role means independently leading

the most challenging parts of data science engagements, producing reliable and

scalable solutions, and serving as a trusted technical advisor to product managers,

engineers, and business stakeholders. You will be recognized for your ability to

translate complex business problems into well-scoped analytical strategies, and for

consistently raising the technical bar across the team.

Who You'll Work With

An outline of the team: You will be part of a collaborative and dynamic data science

team that works closely with data engineers, project managers, solution architects,

and business stakeholders. You will contribute as a high-level technical expert,

helping teams navigate complexity and ensuring that analytical solutions are sound,

scalable, and aligned with business needs.

The role and the team play : The data science team plays a

crucial role in transforming data into strategic assets. As a Principal/Staff Data

Scientist, you will influence the technical direction of projects, contribute reusable

methodologies, and help shape best practices for developing advanced analytical

solutions across multiple engagements.

Who the position reports to: This position reports to the Data Science Team

Manager.

What Makes You a Qualified Candidate / Non-negotiable qualification:

Minimum of 8 years of experience in data science, machine learning, or applied

analytics.

Expertise in programming languages such as Python and SQL.

Strong understanding of advanced statistical methods, machine learning, deep

learning, and GenAI techniques.

Proven ability to scope, architect, and technically lead complex data science

projects without direct management responsibilities.

Excellent communication and presentation skills, with the ability to engage both

technical and non-technical audiences.

What You'll Bring

Advanced Data Analysis and Modeling: Perform highly complex data analysis and

build sophisticated predictive and prescriptive models using advanced statistical,

machine learning, and deep learning techniques.

Technical Leadership: Define analytical approaches, scope data science

components in partnership with PMs, and lead the technical direction of projects

across multiple industries.

Cross-Functional Collaboration: Work closely with data engineers, product

managers, and business stakeholders to align on requirements, solution direction,

and implementation plans.

Data Exploration: Explore large and diverse datasets to uncover insights, evaluate

feasibility, and guide model and feature design.

Model Deployment: Collaborate with engineering teams to implement, optimize,

and maintain machine learning models in production environments, ensuring

scalability, performance, and reliability.

Mentorship: Provide informal technical mentoring, conduct deep code/model

reviews, and guide other data scientists in best practiceswithout direct people

management.

Communication: Present complex findings, trade-offs, and solution paths to

technical teams, business partners, and customer stakeholders in a clear and

concise manner.

Continuous Improvement: Stay current with emerging data science, machine

learning, and GenAI advancements, applying new techniques to enhance solution

quality and accelerate delivery.