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Lead Data Scientist

LexisNexis (RELX)

Lead Data Scientist

LexisNexis (RELX)

Alameda Rio Negro

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Learning and development stipend

Health, dental, and vision coverage

Flexible PTO policy

Parental leave program

Remote work flexibility

Wellness benefits

Required Skills

Python

TensorFlow

Airflow

The Lead Data Scientist will play a pivotal role in driving advanced analytics initiatives and leading a small team of data scientists. This position combines deep technical expertise with leadership responsibilities, ensuring high-quality deliverables and fostering the growth of junior team members. The Lead Data Scientist will define project scopes, maintain timelines, establish best practices and strategic communications, and act as the final approver for project deliverables before client submission—ensuring excellence and consistency.

About the Team

This role is critical to the success of two major workstreams:

  • Quod (MISE): The Lead Data Scientist will personally manage one MISE project end-to-end while *leading another team member working on a second MISE project. Both projects require dynamic and strategic data science analyses to support evolving business needs.
  • Local Products: The Lead Data Scientist will *manage a team member responsible for generating insights from local solution usage and identifying enhancement opportunities, ensuring these insights translate into actionable improvements for our products.

By bridging these areas, the Lead Data Scientist will ensure methodological consistency, accelerate delivery timelines, and strengthen governance across projects.

About the role

This position offers a unique opportunity to shape the future of data-driven decision-making within two critical business streams. By leading high-impact projects and mentoring talent, the Lead Data Scientist will:

  • Drive innovation in advanced analytics approaches.
  • Influence strategic decisions through actionable insights.
  • Establish best practices that scale across teams and projects.
  • Balance leadership responsibilities with hands-on technical execution.

Responsibilities:

  • Act as the primary driver of analytic projects and outcomes, ensuring alignment with business objectives and partner expectations.
  • Define project scope and roadmap, maintain timelines, and establish strategic communication channels to guarantee delivery quality.
  • Lead code reviews and serve as the final approver for project deliverables, setting a high standard for technical rigor.
  • Operate in a consultative capacity with partners, providing guidance and ensuring solutions meet strategic needs.
  • Evaluate and design new frameworks, define methodologies, and implement governance for data science projects.
  • Manage small to medium-sized teams (direct or indirect), mentoring junior members and supporting their technical development.
  • Develop and implement best practices for data science processes, coding standards, and team collaboration.

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About LexisNexis (RELX)

LexisNexis (RELX)

Provides data and technology services, analytics, predictive insights, and fraud prevention for a wide range of industries.

10,001+

Employees

Alpharetta

Headquarters

Reviews

4.2

47 reviews

Work Life Balance

4.1

Compensation

4.6

Culture

4.4

Career

4.2

Management

3.7

86%

Recommend to a Friend

Pros

Flexible remote work options and good work-life balance

Competitive compensation packages with equity

Opportunities for continuous learning and growth

Cons

Organizational changes and restructuring can be disruptive

Internal politics in some teams

Fast-paced environment with tight deadlines

Salary Ranges

58 data points

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · DATA SCIENTIST II

12 reports

$120,900

total / year

Base

$93,000

Stock

-

Bonus

-

$110,381

$132,990

Interview Experience

5 interviews

Difficulty

3.0

/ 5

Duration

14-28 weeks

Experience

Positive 0%

Neutral 80%

Negative 20%

Interview Process

1

Application Review

2

HR Screen

3

Technical Interview

4

Background Check

5

Offer

Common Questions

Technical Knowledge

Past Experience

Behavioral/STAR

Data Analysis