Company OverviewTeragonia develops Analytics Engineering and AI solutions for private equity portfolio companies and founder-owned businesses, supported by a team of technologists, data scientists, and business experts with first-hand private equity experience as investors, operators, and M&amp;A advisors. We create bespoke ‘data-to-dollars’ value creation playbooks using Decision Intelligence Solutions (DIS) that deliver real-time, system-level insights to enhance EBITDA. We supplement the DIS with advisory services to help business leaders operationalize analytics-driven strategies and work closely with deal teams, operating partners, and management to embed analytics in strategic planning and tactical monitoring for timely course corrections.  Our core solutions are designed to support aggressive private equity investment lifecycles and span i) Infrastructure Enhancement, ii) Business Diagnostics, iii) Value Creation, and iv) Exit Prep. In each of the core solutions we leverage cutting edge tools and technology such as SQL, Python, Tableau, Power BI, Dataiku, dbt, and more to translate technical challenges into business value for our clients. We deliver value to clients across three teams: i) Value Creation &amp; Analytics, ii) Data Science &amp; AI, and iii) Engineering. Job SummaryAnalytical Problem-Solving and Predictive Modeling (50%)Utilize a variety of statistical, operations research, data mining, and machine learning techniques to develop, implement, and deploy predictive models in R or Python. This includes analyzing large datasets to identify trends, patterns, and insights that support decision-making processes, as well as writing clean, reproducible code to process data and transform raw datasets into models using algorithms and data science techniques. Design, validate, and implement data pipelines and Machine Learning models in cloud solutions such as Snowflake/AWS/GCP/Azure to support the scalability and deployment of our products and services.Technical Innovation and Product Development (20%)Conduct comprehensive technical research to stay informed about industry trends and apply new data science techniques and methodologies to solve complex business problems. Participate in the development and optimization of proprietary algorithms and machine learning models to enhance product offerings, ensuring they adhere to high standards of efficiency and effectiveness.Cross-Functional Collaboration and Communication (25%)Collaborate closely with a multidisciplinary team of data scientists, software engineers, and business analysts to develop scalable data science applications. Clearly communicate complex data science concepts and the impact of projects to a broad audience, including technical and non-technical stakeholders and clients.Thought Leadership (5%)Demonstrate leadership in technical excellence and problem-solving. Contribute to thought leadership through publishing research, presenting findings at conferences, and engaging with the professional community to enhance visibility and influence in the data science and AI domains.Requirements:At least a Master’s in Data Science or similar mathematical field, and 3 yrs of work experience must include: a) 3 yrs w/Predictive modeling, data mining, statistical analysis, optimization techniques, classification algorithms; b) 3 yrs w/Machine Learning Modeling such as Linear/Logistic Regression, Decision trees, Bayesian Statistics, Cluster Analysis; c) 3 yrs Scientific/ analytical approaches to problem solving, experimentation and investigation; d) 3 yrs w/Manipulating large datasets and writing reproducible code in Python or R; e) at least 1 yr w/Cloud solutions like AWS/Azure/GCP; f) at least 1 yr of deploying and monitoring Machine Learning Models in production; g) flexible telecommuting permitted within normal commuting distance to our Chicago HQ.Location of Employment: Teragonia, Inc. 171 N Aberdeen St, Suite 400, Chicago, IL 60607. Flexible telecommuting permitted within normal commuting distance to our Chicago HQ. Pay range: $150,000 to $190,000 base per year.