Job Description :
Job Title : Data Scientist
Location: Chicago, IL
Job Description :
Responsibilities:
Collaborate with business teams to develop and deliver predictive models.
Help teams in effectively using data to make better decisions.
Ability to apply knowledge of various statistical and machine-learning techniques to lead a wide variety of challenging projects including automating solutions to the complicated problems.
Partner with subject matter experts at the firm by helping explain and predict Real Estate Investment market characteristics (e.g. uncertainty in a market, financial trends etc using internal as well as external data sets.
Analyze data, find trends, and provide visualizations and insights from various data sets.
Apply data analysis, machine learning, predictive modeling, statistics, visualization, and other data science techniques to derive actionable insights.
Develop, create, and implement analytical processes for automated machine driven decision making where human decision making is not scalable or feasible.
Present and explain technical findings to non-technical audiences to promote data-driven decision making.
Document requirements and data sources to enable the design, development, modification and documentation of data science applications and ensure that models and processes are easily understandable and maintainable.
Work with internal and external resources within the parameters of the overall project plan to gather requirements and accomplish objectives, including planning and leading requirement analysis and clarification sessions, and requirements change management.
Assist team members in clearing roadblocks to the original plan as necessary to ensure successful project implementation and following up with the customer to confirm satisfaction with the implementation.
Support testing efforts, including but not limited to: writing, prioritizing and executing test cases, prioritizing and supporting resolution of bugs, coordinating testing cycles with end users and obtaining testing sign-off.
Create and maintain training materials for end users.
Design and implement data quality checks to identify data integrity issues with existing and proposed systems and implement remedial solutions.
Diagnose and resolve user problems and questions, educate users on resolutions, and assist with navigating the platform promptly and professionally. Escalate problems as necessary to ensure awareness and seek assistance with resolution.
Requirements:
Must-haves
Minimum 7 years of experience working as a Data Scientist preferably in a global investment management or financial services organization.
Minimum two years of experience with Azure Machine Learning Services.
Good understanding of Azure Machine Learning Jupyter Notebooks, Azure Kubernetes Services and Azure Dev Ops.
Minimum two years of experience working with Data Science platforms and a deep understanding of Supervised and Unsupervised Machine Learning.
At least four years of experience building production-level machine learning and predictive analytics systems with data pipelines.
Bachelor s degree in Statistics, Mathematics, Physics, Engineering or a related field of study.
Deep understanding of the mathematical fundamentals of machine learning and statistics, with an emphasis on nonparametric, nonlinear methods (e.g., random forests, support vector machines, neural networks) and natural language processing required.
Mastery in conducting analysis in Python.
At least two years of work experience in Microsoft Azure Cloud environment.
Must be self-motivated, organized, and have excellent written and oral communication skills
Demonstrated experience of collaborative work with all stakeholders: functional experts, technology team, 3rd party technology vendors and end users.
Nice-to-haves
Knowledge of R.
Experience with SQL and related data access tools.