AI Engineer​/Data Scientist

SPR helps companies implement the right technology that helps them balance users’ expectations today while planning for tomorrow’s business demands. A technology modernization firm, SPR works together with clients to develop or modernize digital products and platforms.

We’re 100+ strategists, developers, designers, architects, consultants, thinkers, and doers in Chicago. We work with 150 mid- to enterprise-size clients across industries like professional services and manufacturing. We think about the end users and rigorously apply the latest technologies and frameworks to address our clients’ needs. Specializing in custom software development, cloud, data, and user experience solutions, SPR promises to Deliver Beyond the Build by providing proactive advice, sharing knowledge, responding to change in an agile way, and investing time to deeply understand our clients’ business.

We operate in a fun, casual work environment and have great benefits including competitive salary, bonuses, generous vacation time, big fitness incentives, and medical/dental/vision insurance. By joining the SPR team, you’ll be problem solving, working hard and making an impact through your projects – and you’ll be part of a unique culture and rewarded for it.

As a Machine Learning Data Scientist, you will provide direction as needed for clients on predictive analytics projects and machine learning solutions. You must be experienced in the development and/or deployment of machine learning solutions. You must demonstrate a deep understanding of machine learning and statistical analysis & model building. You must be able to demonstrate innovative approaches to complex problems which deliver industry-leading experiences for our clients while working in a team environment.

• Collaborate with clients and cross-functional teams to understand data science and machine learning needs, driving significant business benefits through the integration of ML capabilities and data analytics.
• Execute analytical experiments and prototype AI models to address client needs, ensuring the integration of AI solutions into business processes for optimized performance.
• Utilize advanced algorithms, machine learning, and deep learning techniques to analyze data for trends, patterns, and predictive insights; continually improve models through analysis.
• Implement analytical and AI models in production environments, collaborating with software developers, machine learning engineers, and other stakeholders to ensure seamless integration and scalability.
• Advise executives and business leaders on technology strategies and policy issues related to AI and data analytics, serving as a liaison to convey feedback and enable necessary adaptations.
• Identify, collect, and prepare relevant data sources for analysis, employing a mix of structured and unstructured datasets while ensuring data uniformity and accuracy.
• Research and develop innovative statistical models and ML solutions to solve complex problems across various domains and industries.
• Communicate findings and solutions clearly to all stakeholders, maintaining high ethical standards in data usage and ML applications.
• Stay abreast of the latest developments in data science, AI, and related technologies to enable smarter business processes and more effective problem-solving strategies.
• Serve as a lead strategist, identifying new datasets and AI opportunities that can be leveraged to enhance product capabilities, and work closely with engineering and advanced engineering teams on the development and deployment of data products and AI solutions.

• Motivated, self-starter with ability to learn quickly
• Project management experience and the ability to lead cross-functional teams.
• Advanced degree in a related field is preferred, enhancing depth of knowledge in data science and AI technologies.
• Experience with cloud environments and implementing generative AI models.
• Excellent communication skills, with the ability to articulate complex technical content to non-technical audiences.

• Cloud:
  Azure, AWS, Cloud Foundry, Heroku, Mesos, DC/OS
• RDBMS: SQL…