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Senior Director Data Science Jobs in Indiana (NOW HIRING)

FlixBus

Senior Data Scientist (m/f/d)

Warsaw, IN · On-site

$120 - $180/hr

As a Senior Data Scientist in our Commercial & Marketing Intelligence team at Flix, you can make an ... Brings 5+ years of experience in a data science or quantitative research role, with hands‑on ...

AstraZeneca

Senior Director, Quality

Mount Vernon, IN · On-site

Imagine bringing bold, science-backed decisions to the moments that matter most-how would you raise ... Experience in interpreting and analyzing data so that decisions can be made on product quality.

Pfizer

The Senior Director, Targets and Mechanisms Solutions, as part of the R&D Creation Center ... Mining scientific literature and proprietary data * Supporting reverse-translational efforts from ...

AstraZeneca

Senior Director, Quality

Mount Vernon, IN · On-site

Imagine bringing bold, science-backed decisions to the moments that matter most-how would you raise ... Experience in interpreting and analyzing data so that decisions can be made on product quality.

AstraZeneca

Senior Director, Quality

Mount Vernon, IN · On-site

Imagine bringing bold, science-backed decisions to the moments that matter most-how would you raise ... Experience in interpreting and analyzing data so that decisions can be made on product quality.

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Senior Director Data Science information

What does a senior director of data science do?

A Senior Director of Data Science leads and oversees the data science strategy for an organization, managing teams of data scientists, analysts, and engineers. They are responsible for aligning data initiatives with business goals, guiding advanced analytics projects, and ensuring the effective use of data to drive decision-making. This role often involves collaborating with other executives to develop data-driven solutions, establishing best practices, and setting the vision for how data science supports organizational growth.

How does a senior director of data science typically collaborate with other departments within an organization?

A Senior Director of Data Science frequently partners with leaders from product, engineering, marketing, and business strategy to align data-driven insights with organizational goals. They facilitate cross-functional collaboration by translating complex analytics into actionable business recommendations, ensuring that data science initiatives support top-level priorities. This role often leads a team of data scientists while serving as a bridge between technical teams and non-technical stakeholders, fostering a culture of data-informed decision-making throughout the company.

What are the key skills and qualifications needed to thrive as a senior director data science, and why are they important?

To thrive as a Senior Director Data Science, you need deep expertise in advanced analytics, machine learning, statistical modeling, and a strong educational background in a quantitative field, often with a master's or PhD. Familiarity with data platforms (like AWS, Azure), programming languages (such as Python, R), and leadership in deploying enterprise-level data solutions is vital, along with experience managing large teams. Exceptional strategic thinking, communication, and stakeholder management skills set top candidates apart in this role. These abilities are crucial for driving data-driven business strategies, leading high-performing teams, and ensuring impactful outcomes at the organizational level.

What is the difference between Senior Director Data Science vs Data Science Manager?

AspectSenior Director Data ScienceData Science Manager
ResponsibilitiesOversees multiple teams, sets strategic vision, aligns data science initiatives with business goalsManages day-to-day operations of data science teams, executes projects, and ensures deliverables
Required CredentialsAdvanced degree (Master's/PhD), extensive experience, leadership skillsRelevant degree, experience in managing data projects, technical expertise
Work EnvironmentStrategic, cross-departmental, executive collaborationOperational, team-focused, project management

The Senior Director Data Science typically holds a higher strategic leadership role, overseeing multiple teams and aligning data initiatives with company goals. In contrast, a Data Science Manager focuses on managing teams and executing projects. Both roles require strong technical backgrounds, but the Senior Director emphasizes strategic vision and leadership across departments.

What are popular job titles related to Senior Director Data Science jobs in Indiana?

For Senior Director Data Science jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Senior Director Data Science jobs in Indiana look for?

The top searched job categories for Senior Director Data Science jobs in Indiana are:

What cities in Indiana are hiring for Senior Director Data Science jobs?

Cities in Indiana with the most Senior Director Data Science job openings:

Senior Director Data Science jobs near you
Infographic showing various Senior Director Data Science job openings in Indiana as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 15% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Director, Data Engineering

DWYER INSTRUMENTS, LLC

Michigan City, IN • On-site

$165K/yr

Full-time

Posted 9 days ago

Job description

Description

We are seeking a visionary Director, Data Engineering to architect the "data set of the future." This role is not just about reporting; it is about building the scalable, AI-ready infrastructure that will fuel our next generation of manufacturing innovation. You will move the organization beyond traditional data warehousing to a robust Data Lakehouse architecture, ensuring our enterprise data-from shop floor to point-of-sale-is clean, real-time, and ready for advanced GenAI and predictive modeling. 

The ideal candidate is a technologist who fluently bridges the gap between the plant floor and the front office. You will be responsible for integrating complex operational data with high-velocity sales and commercial data to create a unified ecosystem. By connecting factory efficiency directly to customer demand and market trends, you will enable us to pivot from reactive operations to a truly predictive enterprise.


Key Responsibilities:

  • Architecting the Future: Define and execute a data infrastructure roadmap centered on a Lakehouse architecture that integrates structured and unstructured data, enabling both real-time operational analytics and high-scale AI/ML workloads.
  • AI-Ready Foundation: Establish the data governance, cataloging, and lineage frameworks necessary to power secure, trusted AI models and Large Language Models (LLMs) across the enterprise.
  • Manufacturing Integration: Partner with OT and Engineering teams to ingest and operationalize IIoT and supply chain data, creating a unified data ecosystem that drives predictive maintenance and factory floor efficiency.
  • Modern Data Stack Leadership: Oversee the transition from legacy BI tools to modern, self-service analytics platforms, ensuring the organization has the agility to derive insights from the data lakehouse.
  • Data Ops & Governance: Lead the transition to MLOps and DataOps methodologies, ensuring data quality, security, and compliance in an increasingly automated environment.
  • Strategic Partnership: Collaborate with business unit leaders to identify and prioritize data products that drive measurable top-line growth or operational cost reductions.
  • Team Leadership: Build and mentor a high-performing team of data engineers, ML engineers, and data architects who are comfortable in both cloud-native environments and complex legacy manufacturing systems.

Requirements

Qualifications and Technical Requirements:

  • Strategic Experience: 15+ years in data strategy, architecture, and engineering, with at least 5 years in a leadership role driving organizational change.
  • 5+ years in a leadership role managing data & analytics teams. 
  • Architecture Expertise: Demonstrated experience designing and deploying Lakehouse architectures (e.g., Databricks, Snowflake, or similar) at scale.
  • AI/ML Fluency: Proven experience operationalizing AI/ML models within an enterprise environment; deep understanding of data preparation for LLMs and generative AI.
  • Cloud Proficiency: Extensive experience with Azure (or equivalent cloud hyperscaler) data stacks (e.g., Synapse/Fabric, ADLS Gen2, Azure AI).
  • Tooling: Advanced proficiency in Python, Spark, and SQL; strong experience with CI/CD for data pipelines and infrastructure-as-code.
  • Education: Bachelor's or Master's degree in Computer Science, Data Engineering, or a related technical field.
  • Soft Skills: A "product manager" mindset for data; the ability to translate complex technical architectural debt into business-friendly value proposition

Essential/Preferred Skills:

  • Experience with data governance frameworks and tools. 
  • Exposure to advanced analytics, data science, or machine learning initiatives. 
  • Experience in manufacturing, industrial, or eCommerce environments preferred.

Work Conditions and Physical Requirements:

  • Ability to work in both office and manufacturing environments. 
  • Availability to work outside of core business hours, including nights, weekends, and holidays when required for system upgrades or migrations.
  • Required to sit or stand for long periods of time. 
  • The ability to lift 30-50 lbs without assistance. 
  • Local and/or international travel will be required as needed (10-15%) including some extended stays on location for education or deployments. Must have a valid driver's license and Passport.

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