Senior Data Scientist

ITE Management, a leading investment manager and private equity firm specializing in the acquisition of transportation equipment and asset operating platforms in the infrastructure sector, is seeking an Accounting Manager to join their Finance & Accounting team in New York. Founded in 2014, ITE targets real asset investment opportunities that are cash yielding with downside protection, and benefit from a team with deep, longstanding relationships and financial and operating expertise.  Today, the firm manages over $9bn of assets globally across rail, intermodal, aviation, and emerging technology strategies with office locations in NYC, Chicago and St. Louis.

We are seeking a highly skilled Data Scientist to join our growing team of data scientists at ITE.  As a Data Scientist you will play a critical role in driving data-driven decision-making across our investment strategies, portfolio management, and risk platform. You will work closely with our verticals, business intelligence analysts, data engineers, and other stakeholders to design, develop and deploy data-driven solutions that drive investment decisions and facilitate improved operational outcome at our portfolio companies. You will have the opportunity to bring your ideas to life by building on a foundation of strong internal support, clear vision, engaged users and bright, kind teammates. 

• Analytical Insights:  Conduct in-depth analysis of internal or portfolio company data for deep understanding of underlying linear (and non-linear) dynamical structures. 
• Data Analysis and Modeling: Develop and apply advanced statistical, machine learning and artificial intelligence models in collaboration with internal stakeholders to provide novel insights into operational and investment issues. 
• Risk Analysis and Management: Work closely risk team to develop and apply data-driven risk models 
• ML Ops: Collaborate with data engineers and engineers to design and implement data pipelines, design infrastructure, and enable continuous delivery of high-performing models in production. 
• Product Management: Work with vertical teams and portfolio company users to identify and concisely describe issues to solve, and subsequently translate and document these in terms of scope and functional requirements. 
• Collaboration and Communication: Work closely with cross-functional teams, enabling clear communication and broad understanding of models applied and interpretation of results. 
• Innovation and Best Practices: Stay up to date with emerging trends, technologies and methodologies in data science, machine learning, artificial intelligence, and quantitative analysis. 

Requirements

• Education: Bachelor’s degree in relevant STEM field (e.g., Physics, Mathematics, Data Science, Computer Science); Master’s degree preferred. 
• Experience: At least 3-7 years of experience in a data science role  
• Skills: 

• Strong theoretical background in and practical experience with optimization, statistical techniques, and machine learning & artificial intelligence models 
• Strong programming skills in Python (or R or Julia) and SQL 

• Extensive experience with standard machine learning libraries (e.g., in Python; Numpy, Pandas, SciPy, Scikit-Learn, PyTorch, TPOT, etc.) 
• Working knowledge bringing models to production 
• Experience with data modeling, data warehousing, and ELT processes 
• Excellent communication and presentation skills 

• Cloud Platform: Familiarity with cloud-based business intelligence and data analytics platforms (e.g., Azure, AWS, GCP) – and associated ML platforms (e.g., SageMaker, Vertex) 

Nice to Have 

• Monte Carlo Simulation: Experience building Monte Carlo models for time series simulation; experience with VAR or similar a plus. 
• Domain Expertise: Experience with the analysis or application of data in finance or economics – specific experience with real assets a plus 

Benefits

• Health Care Plan (Medical, Dental & Vision)
• Retirement Plan (401k, IRA)
• Life Insurance (Basic, Voluntary & AD&D)
• Paid Time Off (Vacation, Sick & Public Holidays)
• Family Leave (Maternity, Paternity)
• Short Term & Long Term Disability
• Training & Development
• Hybrid Workplace
• Free Food & Snacks
• Wellness Resources