Additionalinformation

Additional Information

At Logic20/20, we believe in recognizing and rewarding exceptional talent. Logic20/20 offers a competitive compensation package, with a target base salary range of $178,200 - $200,000 for this role. The final base salary offered is dependent on factors such as relevant experience, skills, qualifications, and location. Eligible employees may also qualify for performance-based bonuses and other incentives.

All your information will be kept confidential according to EEO guidelines.

Learn more about life at Logic20/20!

Visit our Life at Logic page to explore our culture, benefits, and what makes Logic20/20 a great place to grow your career!

Core Values

At Logic20/20, we are guided by three core values: Drive toward Excellence, Act with Integrity & Foster a Culture of We. These values were generated and agreed upon by our employees—and they help us pursue our goal of being one of the best companies to work for and to work with. Learn more at https://www.logic2020.com/company/our-values.

Equal Opportunity Statement

We believe that people should be celebrated: for their talents, ideas, and skills, but most of all, for what makes them unique. We prohibit harassment and/or discrimination based on age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status, or any other basis as protected by federal, state, or local law.

To learn more about our DE&I initiatives, please visit: https://www.logic2020.com/company/diversity-equity-inclusion

Privacy Policy

During the recruitment and hiring process, we gather, process, and store some of your personal data. We consider data privacy a priority. For further information, please view our company privacy policy.

Companydescription

Company Description

We’re a ten-time “Best Company to Work For,” where intelligent, talented people come together to do outstanding work—and have a lot of fun while they’re at it. We offer a solution-focused environment full of collaboration and dedication to our goals and to each other. You’ll have the opportunity to drive your own success in a supportive, globally connected environment. From advanced tools and technology to an immersive company culture, working at Logic20/20 means working on the leading edge, with a community of the right people around you.

About the team

The Logic20/20 AI & Analytics team is where skilled professionals in data engineering, data science, and visual analytics join forces to build simple solutions for complex data problems. We make it look like magic, but for us, it's all in a day's work. As part of our team, you'll collaborate on projects that help clients spin their data into a high-performance asset, all while enjoying the company of kindred spirits who are as committed to your success as you are. And when you're ready to level up in your career, you'll have access to the training, the project opportunities, and the mentorship to get you where you want to go.

"We build an environment where we really operate as one team, building up each other's careers and capabilities." – Adam Cornille, Managing Director, AI & Analytics

Jobdescription

Job Description

Logic20/20 is seeking a Lead Data Scientist to join our Advanced Analytics & AI practice. This role will lead the development of innovative data science solutions that help clients solve complex business challenges through advanced analytics, machine learning, and data-driven decision-making.

The ideal candidate combines deep technical expertise with strong consulting and stakeholder management skills. You will work closely with cross-functional teams to design analytical solutions, guide project delivery, mentor team members, and help clients translate data into actionable business outcomes.

This is an opportunity to work on high-impact initiatives across industries while contributing to the growth of Logic20/20's data science and analytics capabilities.

What you’ll do:

• Lead the design, development, and deployment of advanced analytics and machine learning solutions.
• Partner with clients and stakeholders to understand business objectives and translate requirements into analytical approaches.
• Analyze large, complex datasets to uncover insights, identify opportunities, and support strategic decision-making.
• Develop and validate statistical, predictive, and machine learning models.
• Communicate technical findings and recommendations to executive and non-technical audiences.
• Provide technical leadership and mentorship to data scientists, analysts, and cross-functional project teams.
• Collaborate with data engineering, product, and business stakeholders to support end-to-end solution delivery.
• Establish best practices for model development, testing, validation, documentation, and performance monitoring.
• Contribute to project planning, solution architecture, estimation, and delivery execution.
• Support business development efforts through technical expertise, solution ideation, and client presentations.

Qualifications

• 10-15 years of experience as a data scientist, designing, building, and validating production-grade machine learning models using Python and SQL.
• Experience leading complex analytics initiatives and driving technical decision-making.
• Experience building solutions in Azure (Azure Machine Learning, MLflow, Azure Synapse, Microsoft Fabric).
• Strong client-facing consulting and stakeholder management experience.
• Exceptional communication and presentation skills, with the ability to explain complex concepts to both technical and business audiences.
• Experience working across the full data science lifecycle, from problem definition through model deployment and adoption.
• Demonstrated success leading projects in enterprise environments.

Preferred Qualifications

• Consulting experience and/or experience in utilities, energy, infrastructure, asset management, or reliability-focused industries is highly preferred.
• Experience developing risk, reliability, asset health, anomaly detection, or failure prediction models.
• Experience supporting model governance, validation, explainability, and operationalization efforts.
• Master’s degree or PhD in machine learning, statistics, computer science, data mining, math, or any quantitative discipline.