Senior Data Scientist

Job Summary - Job Description

The Senior Data Scientist is an advanced individual contributor who provides technical or functional leadership across data science. This role leads complex work spanning statistical modeling, experimentation, predictive analytics, machine learning, and insight generation, establishes direction and standards, resolves high-impact challenges, and influences cross-functional outcomes without direct people-management accountability.

DU Tech is looking for a Senior Data Scientist to provide advanced expertise and individual-contributor leadership across data science. This role will lead complex work, shape solution direction, mentor others through influence, and partner across teams to deliver reliable, scalable, secure, and measurable outcomes.

Job Responsibilities

Delivery & Execution

• Lead complex data science initiatives and provide advanced subject-matter expertise.

• Define or improve approaches, standards, and reusable patterns spanning statistical modeling, experimentation, predictive analytics, machine learning, and insight generation.

• Translate enterprise priorities into technical or functional direction and high-impact deliverables.

• Lead reviews and resolve complex risks, dependencies, and trade-offs.

• Drive quality, security, privacy, reliability, automation, reuse, and continuous improvement.

• Serve as a trusted expert during critical delivery or operational issues.

Support & Enablement

• Influence product, business, architecture, security, data, and technology stakeholders without direct authority.

• Mentor practitioners and strengthen capability through reviews, standards, and knowledge sharing.

• Communicate direction, risks, trade-offs, and recommendations to leadership and technical audiences.

• Stay current on emerging practices and relevant industry developments.

Requirements

• Bachelor's degree in

Computer Science, Information Technology, Engineering, Design, Analytics, Business, or a related discipline

• 4 to 9 years of relevant

experience in data science or a closely related discipline

• Experience with statistical

modeling, experimentation, predictive analytics, machine learning, and insight generation

• Experience leading complex

initiatives and influencing decisions without direct authority

• Knowledge of Python or R,

statistics, experimentation, predictive modeling, machine learning, SQL, and visualization

• Experience collaborating

across business and technology teams

• Strong analytical, problem-solving, written, and verbal communication

skills

Preferred Qualifications & Interests (PQIs)

• Master's degree in a related technical or business field is preferred

• Advanced knowledge of Python or R, statistics, experimentation, predictive modeling, machine learning, SQL, and visualization

• Experience with enterprise-scale cloud, data, digital, retail, pharmacy, healthcare, or customer technology environments

• Experience working with global teams, managed service partners, or distributed delivery models

• Relevant industry, cloud, agile, product, architecture, data, security, design, or technology certifications are preferred

Key Primary Skills

• Completes programming and performs testing and debugging applications

"• Bachelor’s degree in computer science, Engineering, Information Systems, or related field.

• 3+ years of experience in data engineering

• Strong SQL, PySpark/Scala Spark development experience.

• Design ETL/ELT pipelines using PySpark, SQL, Spark Structred Streaming, and Databricks workflows - Lakeflow.

• Capable of developing streaming data pipelines using PySpark APIs / Scala Spark APIs (version 3+) , Lakeflow concepts, Unity Catalog features

• Capable of coding with or without AI assistants

• Experience designing and supporting data pipelines; working in cross-functional or matrix organizations.

• Ability to communicate technical concepts effectively.

• Willingness to travel up to 10% as needed. "

Secondary Skills

Interpret and apply data in analyses and explains findings to business audiences to improve products and processes, or to discover the next breakthrough

Interpret and apply data in analyses and explains findings to business audiences to improve products and processes, or to discover the next breakthrough