Are you passionate about client experience, and data analytics, especially descriptive and predictive analytics? If so, come join our team where you will work directly with a number of teams, including client experience, product development, sales, marketing, and solutions management to derive data driven insights that will impact the business and empower the investment management industry.
You will build statistical models to derive knowledge from existing and new data. The teams will rely on your expertise to build a common data science infrastructure that will house statistical models and enable scientists to run experiments on a large variety of projects. The data science infrastructure you help build, the models you develop, and the predictive analytics you create will be used by business leaders to create value for our clients, improve client experience, and inform the strategic direction of the business.
Prior experience in prescriptive analytics, such as optimization, is a plus.
Your Key Responsibilities
- Manage and execute entire project from start to finish (problem solving, data gathering, data manipulation, predictive modeling, and key stakeholder engagement)
- Demonstrate technical knowledge on feature engineering, effective exploratory data analysis, and building statistical models
- Implement code (Python, R, Scala, SQL, etc.) for analyzing data and building machine learning and econometric models to solve specific business problems
- Translate analytic insights into actionable recommendations
- Contribute to the scientific roadmap
- Research, learn, and adapt new modeling techniques and procedures to solve complex business problems
- Build a common data science infrastructure that will house statistical models and enable scientists to run experiments on a large variety of project
- Produce and maintain technical documents
- Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related field; or data science practitioner for 3+ years
- Solid experience in descriptive analytics (reporting, querying, scorecards, dashboard building, visualization, presentations, etc.)
- Experience in data mining and data engineering techniques (gathering, preparing, cleansing, and transforming data) to find patterns and build models
- 2+ years of experience in predictive analytics (statistical data modeling, predicting what customers would do, how customers would respond to marketing campaigns, how client experience would improve, etc.)
- Experience in supervised methods (classification, regression, causal modeling) and unsupervised methods (clustering, co-occurrence grouping, profiling)
- Experience programming in R, Scala, Python (Django, Flask, Pyramid, etc.), or similar languages and maintaining code repositories
- Experience formulating and testing hypotheses using tools like Jupyter notebooks, R, Julio, etc.
- Create prototype machine learning or statistical models using open-source packages, such as SciKit Learn, PyTorch, Tensorflow, Stan, or equivalent
- Excellent verbal and written communication skills
- Experience in building prescriptive analytics (optimization, randomized test, designing experiments, simulations, finding optimum price, etc.)
- Experience in building business intelligence automation using platforms such as Salesforce, Cognos, QuickSight, Tableau, or similar
- Working knowledge of optimizers (i.e. Gurobi) or solvers (GLPK, LP_Solve)
- Previous experience integrating multiple applications and data APIs
- Knowledge of software development life cycle (coding standards, code reviews, source control, build processes, testing, and operations)
- Leadership skills and ability to work well with others