Senior Data Scientist & ML Technical Lead

Theinsidejob; Germany (OH); On-site; USD 140,000 - 210,000; Full time

Job summary

Theinsidejob is seeking a senior data science leader to provide technical guidance across multiple ML initiatives. You will shape modelling approaches, align solutions with business priorities, and drive production readiness and scalability.

You will mentor teams, enforce best practices, and partner with architecture and engineering to ensure robust, end-to-end ML deployments while communicating complex decisions clearly to stakeholders.

Qualifications

• Extensive experience delivering production-grade data science solutions.
• Senior technical lead experience with reviews or sign-off.
• Strong ability to deploy ML solutions on cloud platforms (GCP/AWS/Azure).
• Advanced Python and SQL skills.
• Deep knowledge of ML techniques: regression, classification, clustering, time-series.
• Experience in deployment and lifecycle management of ML models.
• Understanding of data warehousing and modern data architecture.
• Excellent ability to communicate technical decisions to non-technical stakeholders.

Responsibilities

• Act as a technical lead for data science across multiple initiatives.
• Translate priority use cases into production-ready DS solutions.
• Provide hands-on leadership across the DS lifecycle from framing to deployment.
• Define and embed technical standards for experimentation and reproducibility.
• Review designs and provide clear technical direction and sign-off.
• Mentor data scientists on complex challenges.
• Collaborate with Data Architecture, ML & Data Engineering, and BI teams.
• Evaluate new techniques and adoption strategies.
• Communicate technical assumptions, risks, and trade-offs to stakeholders.

Skills

Production ML

Senior lead

Python

SQL

Cloud platforms

ML techniques

Deployment lifecycle

Data warehousing

Communication

Job description

Theinsidejob is seeking a senior data science leader to provide technical guidance across multiple ML initiatives. You will shape modelling approaches, align solutions with business priorities, and drive production readiness and scalability.

You will mentor teams, enforce best practices, and partner with architecture and engineering to ensure robust, end-to-end ML deployments while communicating complex decisions clearly to stakeholders.