
Principal Engineer - Data Analytics IV
Net2Source · Oshkosh, WI · Hybrid
Strong hiring record · median 12 days open
All reasons
In its favour
- Still listed on the employer's own board
Join a Global Leader in Workforce Solutions – Net2Source Inc.
Who We Are
Net2Source Inc. isn't just another staffing company, we're a powerhouse of innovation, connecting top talent with the right opportunities. Recognized for 300% growth in the past three years, we operate in 34 countries with a global team of 5,500+. Our mission? To bridge the talent gap with precision—Right Talent. Right Time. Right Place. Right Price.
Job Title
Principal Data Scientist
Location
Oshkosh, Wisconsin, or New Hudson, Michigan (HYBRID - 3 days onsite and 2 remote)
Direct Hire + Benefits + 10% Bonus
Core requirements
- 8+ years of experience is the manager's expectation for the principal level.
- Proven experience delivering analytics or AI projects tied to business outcomes, with demonstrated impact on revenue growth or margin improvement.
- Strong business or domain expertise in manufacturing, supply chain, operations, sales, or lifecycle services. Candidates from fields such as automotive, energy, Client, or healthcare may also fit if they bring relevant business acumen.
- Experience working between business teams and IT/analytics: engaging senior business leaders (AVP level and above), gathering requirements, translating them into technology problems, and explaining solutions back to the business.
- Strong communication, business acumen, and ability to influence, including handling challenging conversations with senior leaders.
- Demonstrated experience mentoring junior team members.
Preferred
- Awareness of and openness to market-based or vendor-led AI solutions—not assuming every solution must be built in-house.
- A consultative, outcome-focused approach: able to deliver a solution by building it, partnering with a vendor or consultancy, or using managed services.
YOUR IMPACT
- Define the technical roadmap and architecture for enterprise AI/ML initiatives aligned with business objectives.
- Partner with executive leaders across Access, Defense, Fire & Emergency, and Commercial segments to identify high-value analytics opportunities.
- Champion best practices for MLOps, model governance, ethical AI, and scalable data products.
- Lead the end-to-end design, development, and deployment of complex predictive, prescriptive, and generative AI models.
- Translate complex business challenges into production-ready data science frameworks
- Provide technical mentorship and guidance to senior, mid-level, and associate data scientists and machine learning engineers.
- Collaborate closely with data engineering, cloud infrastructure, and software teams to ensure robust model deployment and monitoring.
- Communicate complex analytical concepts and ROI metrics clearly to technical and non-technical stakeholders.
QUALIFICATIONS
- Experience with industrial IoT, telematics, edge AI, or time-series sensor data from heavy machinery, automotive, or aerospace domains.
- Background in computer vision (CV), autonomous vehicle tech, or robotics.
- 8+ years of progressive levels of responsibility in analytics and AI in any business organization
- Programming: Advanced proficiency in Python and SQL; experience with R, Scala, or C++ is a plus.
- ML/AI Frameworks: Deep experience with Scikit-learn, PyTorch, TensorFlow, XGBoost, and Hugging Face.
- Big Data & Cloud: Strong hands-on experience with cloud ecosystems (Azure or AWS), Databricks, Snowflake, and Apache Spark.
- MLOps & DevOps: Demonstrated expertise in Docker, CI/CD pipelines, MLflow, model registry, monitoring, and automated retraining workflows.
- Familiarity with Agile/Scrum delivery frameworks within large enterprise environments.
Industry Experience
- Experience working in a portfolio company with multi-business units; preferably a manufacturing company
- Bring domain expertise in Supply chain, Manufacturing or Lifecycle services
- Consulting (nice to have)
Personal Characteristics
- Exceptional problem-solving, strategic thinking, and architectural design skills.
- Strong business acumen with the ability to link algorithmic output to measurable industrial impact
- AI and Business savvy person who understands how businesses make money and how AI tools can help businesses solve real business problems
- Strong EQ with the demonstrated ability to relate to both data scientists and business leaders
- A strong listener with strong written, and verbal communication skills
- Change agent who can lead via inspiration and motivation, subject knowledge, and demonstrating a "roll up your sleeves” approach to working
Preferred Qualifications
- Bachelor's degree in data science, mathematics, economics, statistics, engineering, or information management
- Advanced Degree (MBA and/or PhD)
- Background in computer vision (CV), autonomous vehicle tech, or robotics.
- Familiarity with Agile/Scrum delivery frameworks
Why Work With Us?
We believe in more than just jobs—we build careers. At Net2Source, we champion leadership at all levels, celebrate diverse perspectives, and empower you to make an impact. Think work-life balance, professional growth, and a collaborative culture where your ideas matter.
Our Commitment to Inclusion & Equity
Net2Source is an equal opportunity employer, dedicated to fostering a workplace where diverse talents and perspectives are valued. We make all employment decisions based on merit, ensuring a culture of respect, fairness, and opportunity for all, regardless of age, gender, ethnicity, disability, or other protected characteristics.
Awards & Recognition
- America's Most Honored Businesses (Top 10%)
- Fastest-Growing Staffing Firm by Staffing Industry Analysts
- INC 5000 List for Eight Consecutive Years
- Top 100 by Dallas Business Journal
- Spirit of Alliance Award by Agile1
Ready to Level Up Your Career?
Click Apply Now and let's make it happen.
Skills
- MLOps
- Generative AI
- Machine Learning
- Computer Vision
- Python
- SQL
- R
- Scala
- C++
- scikit-learn
- PyTorch
- TensorFlow
- XGBoost
- Hugging Face
- Azure
- AWS
- Databricks
- Snowflake
- Spark
- Docker
- MLflow
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