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Director Data Science Startup Jobs in Minnesota (NOW HIRING)

IWCO Direct

Data Science Operations Analyst

Chanhassen, MN · On-site

$90K - $95K/yr

The Data Science Operations Analyst plays a key role in supporting data-driven direct marketing campaigns that deliver highly targeted, performance driven results. This position is responsible for ...

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Director Data Science Startup information

What are some unique challenges a Director of Data Science faces in a startup environment?

As a Director of Data Science in a startup, you will often need to balance hands-on technical work with strategic leadership, since resources and team sizes are usually limited. You'll likely be tasked with building and mentoring a team from the ground up, establishing best practices, and aligning data initiatives with fast-changing business goals. Additionally, you may need to advocate for data-driven decision-making across non-technical teams and adapt quickly as the company's priorities shift. This environment fosters rapid professional growth but requires flexibility, strong communication skills, and a willingness to wear multiple hats.

What is the difference between Director Data Science Startup vs Data Scientist?

AspectDirector Data Science StartupData Scientist
Required CredentialsAdvanced degree (Master's/PhD), leadership experienceBachelor's or Master's in Data Science, Computer Science, or related field
Work EnvironmentLeadership role overseeing teams, strategic planningHands-on data analysis, model development, research
Employer & Industry UsageStartups, tech companies, innovation-driven firmsVaries from startups to large corporations, research labs
Search & Comparison IntentUnderstanding leadership roles, strategic responsibilitiesTechnical skills, project work, data analysis

The Director Data Science Startup typically holds a leadership position with strategic oversight and team management responsibilities, requiring advanced degrees and experience. In contrast, a Data Scientist focuses on technical data analysis and model development, often with less emphasis on leadership. Both roles are common in startup environments and tech industries, but they differ significantly in scope and responsibilities.

What are the key skills and qualifications needed to thrive as a Director of Data Science at a Startup, and why are they important?

To thrive as a Director of Data Science at a startup, you need deep expertise in statistical modeling, machine learning, and data strategy, often supported by an advanced degree in a quantitative field. Familiarity with tools like Python, R, SQL, cloud platforms (e.g., AWS, GCP), and experience with data pipeline architectures are typically required. Strong leadership, communication, and business acumen are vital soft skills for aligning data initiatives with startup objectives and motivating cross-functional teams. These skills are crucial for driving product innovation, scaling data operations, and delivering actionable insights in a fast-paced, resource-constrained environment.

What does a Director of Data Science do at a startup?

A Director of Data Science at a startup leads the development and execution of data-driven strategies, overseeing teams of data scientists and analysts to drive business growth. They are responsible for aligning data initiatives with the company's goals, building predictive models, and ensuring the integrity and scalability of data solutions. This role often involves close collaboration with engineering, product, and executive teams to translate business needs into actionable data projects. Additionally, they help shape the data culture and mentor team members in a fast-paced, resource-constrained environment.
What are the most commonly searched types of Data Science Startup jobs in Minnesota? The most popular types of Data Science Startup jobs in Minnesota are:
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Director Data Science Startup jobs near you
Director, Data & Information Architecture

Director, Data & Information Architecture

Pivot Bio

Minnetonka, MN

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 4 days ago

Job description

About Pivot Bio

Fueled by an innovative drive and a deep understanding of the soil microbiome, Pivot Bio is pioneering game-changing advances in agriculture. Our products harness naturally occurring microbes to provide nutrients to crops, helping farmers improve yields while reducing environmental impact.

Pivot Bio is seeking a Director, Data & Information Architecture to define and steward the enterprise information backbone connecting Product Innovation, Agronomy, Manufacturing, Commercial, and Digital products. This role is responsible for establishing canonical data models, domain boundaries, data contracts, lineage standards, and governance patterns that enable trustworthy, decision-grade data across the enterprise. Unlike traditional platform-focused data architecture roles, this position is centered on information architecture: designing durable semantic models, traceability frameworks, and evidence systems that support product performance analysis, scientific discovery, operational execution, and AI-enabled decision making.

What Success Looks Like

  • Define canonical enterprise data models spanning R&D, Agronomy, Manufacturing, Commercial, and Digital domains.
  • Establish domain ownership, data contracts, lineage, and reconciliation standards.
  • Design logical and physical Lakehouse models supporting Silver and Gold layers.
  • Create traceable, reproducible evidence systems capable of supporting scientific and commercial decision making.
  • Provide a phased architecture roadmap for modernization and migration of existing data assets.
  • Enable trustworthy AI and analytics through strong semantic foundations.

Key Responsibilities

  • Own enterprise information architecture strategy and standards.
  • Design canonical models, master data relationships, and cross-domain integration patterns.
  • Define semantic standards for observations, results, recommendations, outcomes, and evidence.
  • Lead logical and physical data modeling efforts within Databricks Lakehouse.
  • Establish metadata, lineage, versioning, and traceability frameworks.
  • Partner with Product, Engineering, Data Science, Manufacturing, and Commercial teams to translate business requirements into durable data models.
  • Review architecture designs and validate implementations through hands-on modeling, SQL analysis, and proof-of-concept work.
  • Drive data governance practices focused on quality, stewardship, reproducibility, and trust.

Preferred Experience

  • 10+ years in Data Architecture, Information Architecture, or Enterprise Data Modeling.
  • Deep expertise in conceptual, logical, and physical data modeling.
  • Experience with canonical modeling, Data Vault, metadata management, MDM, and lineage.
  • Hands-on experience with Databricks, Snowflake, or modern Lakehouse platforms.
  • Strong SQL skills and ability to validate models directly against data.
  • Experience in regulated, scientific, manufacturing, healthcare, life sciences, or evidence-sensitive environments preferred.
  • Demonstrated ability to balance governance rigor with pragmatic execution.

What We Are Not Looking For

This role is not primarily a cloud infrastructure architect, integration engineer, or BI/reporting architect position. Success requires deep information architecture capability, including semantic modeling, domain design, lineage, traceability, and enterprise data stewardship.

Must be authorized to work in the United States.

What We Offer: 

  • Incentive Bonus Plan
  • Competitive package in a disruptive startup 
  • Stock options 
  • Health/Dental/Vision insurance with employer-paid premiums 
  • Life, Short-Term and Long-Term Disability policies 
  • Employee Assistance Program with free referrals and discounts 
  • 401(k) plan, 3% Match 
  • Commuter benefits 
  • Annual Training & Development support 
  • Flexible vacation policy with a generous holiday schedule 
  • Exciting opportunity to work with a talented and fun team

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