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 teams—without 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 practices—without 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.