Data Scientist at Green Dot

We’re looking for talented professionals, anywhere in the United States, to join us in bringing smart money management and payment solutions to everyone’s fingertips.At Green Dot, we are evolving to a new and permanent “Work from Anywhere” model designed to maximize the benefits of remote work, promote and enable a strong culture of performance and connectedness, and attract the best and brightest talent who align with our entrepreneurial spirit and mission.<<>><<>><<>><<>><<>><<>><<>><<>><<>><<>> JOB DESCRIPTIONThis is an exciting opportunity to apply data science techniques and drive growth and revenue of Green Dot’s Business, Enterprise-wide. Our data science team works on several projects across the entire company including Churn Modelling and Customer Scoring for Marketing efforts, Revenue Prediction Modeling for Accounting and Finance and Cash Advance Customer Modeling for our Award-Winning Tax Products.We are looking for candidates who are passionate about leveraging data science techniques to solve business problems and supplying stakeholders with actionable insights/decisions.  The ideal candidate must be a self-starter who is able to deliver high quality work within tight deadlines and potentially propose/develop innovative solutions as well.  The candidate will be reporting to the Lead Data Scientist within our Data Analytics department.Job Responsibilities 
Maintain and train existing business-critical models and support the Data Science team.
Develop and implement data science/advanced analytics enabled solutions to drive business outcomes and goals.
Own and deliver predictive modeling/analytics projects of small or moderate scope or manage tasks on complex data science projects.
Define, write queries, and extract and transform data sets to create features for modeling and/or generate actionable insights using various tools (SQL Server, Python, R)
Collaborate with other Data Scientists and Analytics teams across the Enterprise to help ensure a cohesive and strategic implementation of our data capabilities.
Identify meaningful insights from large data and metadata sources; interpret and communicate insights and findings from analysis and experiments to product, service, and business managers. 
Collaborate with business stakeholders as per project needs and communicate results of the models/analytical solutions developed).
Learn and grow in the role over time, utilizing the multitude of available resources (people and technologies) and become a strategic leader, helping to grow our Data Science capabilities.
Perform other duties as needed.

Job Requirements
Bachelor’s degree in a quantitative, technical, or financial discipline required. Masters in a similar field is a plus.
2 or more years of experience in data science or advanced analytics based on education/experience.
Solid understanding of data science and statistical modeling techniques such as classification, clustering, regression, decision trees etc.
Experience with Sagemaker, Lambda or other services for model deployment and monitoring.
Experience with various machine learning frameworks and libraries such as scikit-learn, TensorFlow, PyTorch, Keras, etc.
Knowledge of machine learning concepts and techniques such as supervised and unsupervised learning, regression, classification, neural networks, clustering, etc.

Proficiency writing SQL queries (i.e. Amazon Redshift, MS-SQL Server, etc.) and working with large data sets.
Experience using Python (required), other statistical tools (such as R) and AWS Sagemaker (preferred but not mandatory).
Experience developing and/or maintaining business reporting using business intelligence or reporting tools such as Excel, Tableau, MicroStrategy or similar tools.
Proactive work style, progressive thinking skills, strong work ethic, communication, and problem-solving skills.


Experience with Sagemaker, Lambda and other AWS services for model deployment and monitoring
Experience with various machine learning frameworks and libraries such as scikit-learn, TensorFlow, PyTorch, Keras, etc.
Knowledge of machine learning concepts and techniques such as supervised and unsupervised learning, regression, classification, neural networks, clustering, etc.


POSITION TYPERegular<<>><<>><<>><<>><<>><<>><<>><<>><<>><<>>Green Dot promotes diversity and provides equal opportunity for all applicants and employees. We are dedicated to building a company that represents a variety of backgrounds, perspectives, and skills. We believe that the more inclusive we are, the better our work (and work environment) will be for everyone. Additionally, Green Dot provides reasonable accommodations for candidates on request and respects applicants' privacy rights.