Job DescriptionAs a Lead Data Scientist, you'll transform data into powerful insights capable of driving enlightened decision-making. You'll work closely with the client to understand their business needs, then frame those needs as statistical problems and solve them with leading-edge methodologies. Along the way, you'll lead a diverse team of machine learning engineers, data engineers, analysts, and technical project managers, each contributing their own unique skill sets in creating world-class solutions.
What you'll do:- Lead the development of computer vision models.
- Design and improve machine learning approaches in environments with limited training data.
- Explore and apply advanced techniques, including vision-language models (VLMs), synthetic data generation, and traditional data labeling workflows.
- Build and support solutions within an Azure-based development environment.
- Collaborate with cross-functional team members supporting the broader computer vision and data labeling effort.
- Serve as a trusted advisor and subject matter expert to clients by taking a hands-on approach in maturing the client's data science capabilities to create value within their business.
- Develop custom solutions to unique business problems using modern toolsets and platforms, including Python, SQL, Azure, and AWS.
- Participate in internal initiatives, such as interview support, client brainstorming, and POC development, to foster a culture of growth and collaboration.
Qualifications- 10-15 years of experience as a data scientist developing machine learning models using Python.
- Experience leading teams.
- Strong hands-on experience in computer vision.
- Experience with Azure.
- Consulting experience and/or experience working in the utilities industry is highly preferred.
Additional InformationAt 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 $188,100The 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.
