Data scientist

Summary We re looking for a dynamic Data Science with machine learning experience to join the data science team at Gainwell Technologies. You will have the opportunity to work as part of a cross:functional team to define, design and deploy frameworks for data collection, normalization, transformation, storage and reporting on AWS to support the analytic missions of Gainwell and its clients. Your role in our mission Essential Job Functions :Lead large data science projects and deliver innovative technical solutions to solve problems and improve business outcomes :Design, develop, test, validate, and deploy Machine Learning (ML) /Statistical models to not only learn from our vast amounts of data but to build new products :Work closely with engineers to deploy models to production both in batch and real time while systematically tracking model performance :Build complex data sets from multiple data sources and write complex data flows using SQL, Spark and scripting languages (e.g., Python, R) :Use data visualization tools (e.g., Tableau, Kibana, Zeppelin) to share ongoing insights :Present findings to both technical and non:technical audiences :Function as a subject matter expert on machine learning and predictive modeling :Assist engagements with key business stakeholders in discussion on business opportunities :Be an evangelist driving wider adoption of analytics across the enterprise What were looking for :5+ years of industry experience in Data Science/Machine Learning as a mid:senior data scientist/technical lead developing ML models with business impact :5+ years hands:on, industry experience with data and languages such as e.g. SQL, Python, R, Scala :5+ years experience in data analysis using Relational Databases, SQL, and Hadoop :2+ years experience in leading complex data science projects from dev to prod, end:to:end :2+ years experience in designing and implementing ML pipelines in production environments :2 years of experience with Apache Spark (including Datasets, SparkML) and other Big Data analytics tools (e.g. Hadoop ecosystem, PySpark, GraphML) :Experience with 2 or more additional modeling techniques (i.e. Natural Language Processing, Deep Learning, Time Series Analysis, Optimization algorithms) is a plus :Experience with one or more deep learning libraries (e.g., TensorFlow, PyTorch, Caffe) is a plus :Experience implementing solutions in a cloud environment (AWS or Azure) is a plus :Experience from working in Lean and Agile environments is a plus What you should expect in this role :Fast:paced,challenging and rewarding work environment. :Hybrid Office environment. :Will require late evening work to overlap US work hours.