- One project they will support is the Lifetime Engagement space.
- They will be using data science to identify customers who would be interested in doing certain financial transactions- crossover, invest more, use $$ for more active investment.
- This is a project to make more money for the firm and to help customers to reach financial goals.
- They will be creating models to use machine learning to identify that customer, then using that info to do outreach to customer by contact and marketing towards them.
- The Company is seeking a hands-on data scientist with financial or healthcare services industry experience.
- The associate’s key differentiating abilities will be outstanding data science, programming and problem-solving skills.
- Absolutely critical is individual's ability to carry an initiative from ideation to execution.
The Purpose of Your Role
You will work with peer data scientists and business stakeholders to provide data analysis, machine learning and analytic thought leadership, develop Machine Learning and / or Deep Learning based Models and production-quality machine learning pipelines for specific use cases. You will also work closely with Product Managers and on various aspects of model pipeline rollouts.
At the Company, we are passionate about making our financial expertise broadly accessible and effective in helping people live the lives they want. We are a privately held company that places a high degree of value in building and encouraging a work environment that attracts the best talent and reflects our commitment to our associates. We are proud of our diverse and expansive workplace where we respect and value our associate for their outstanding perspectives and experiences.
- A natural programmer, with demonstrated industry experience statistics, machine learning, data modeling and building associated pipelines
- Experience with one or more of the following tools/frameworks – python, scikit-learn, nltk, pandas, NumPy, R, PySpark, Scala, SQL/big data tools, TensorFlow, PyTorch, etc.
- 3+ years of data science experience in financial, healthcare or digital services industries.
- Analytic Skills: In addition to core regression, classification and time series skills that accompany the data science role, experience with A/B testing, causal inference and experimentation methods are preferred
- Education– At least one advanced degree (Master or PhD level) in a technical or mathematically-oriented discipline, e.g., coursework or experience in fields such as statistics, machine learning, computer science, applied mathematics, econometrics, engineering, etc.
- Good communication and problem solving skills
- Strong written and oral communications/presentations with the ability to produce a variety of business documents (business requirements, technical specs, slide presentations, etc.) that demonstrate command of language, clarity of thought, and orderliness of presentation