Data Scientist

Data ScientistContract to hire Data Scientist position with a major financial firm. Hybrid 3 days/week in Newark, NJ. Responsible for the hands-on development of sophisticated data science solutions comprising the portfolio developed by the Director Data Scientist and the technical requirements specified by the Director Data Scientist. Perform hands-on data analysis, model development, model training, model testing, model deployment. Continuously research new methods for problem solution, including new algorithms, modeling techniques, and data analytics techniques. Write production-level code and partner with machine learning engineers to push development code into production. Partner with machine learning engineers to productionized machine learning models. Partner with data engineers to build data pipelines. Partner with software engineers to integrate solutions with business platforms. Work closely with the business and data science lead to recommend and develop models for customer engagement and wellness use cases. Manage external vendors in the execution of the data science development process. This position is hybrid to Newark, NJ.The skills and expertise you bring: Exercises judgment within broadly defined practices and policies in selecting methods, techniques, and evaluation criteria for obtaining results. Knowledge of business concepts, tools and processes that are needed for making sound decisions in the context of the company's business. Create and test hypotheses for customer engagement and wellness programs. Experience in research, designing experiments (ex: A/B testing), working with claims and customer experience data. A behavior science background is preferred but not required. Ability to learn creative skills and knowledge on an on-going basis through self-initiative and solving challenges. Excellent problem solving, communication and collaboration skills. Applied experience with several of the following:Data Acquisition and Transformation: Acquiring data from disparate data sources using API's, SQL and NoSQL. Transform data using SQL, NoSQL, and Python. Visualizing data using a diverse tool set including but not limited to Python and R.Database Management System: Knowledge of how databases are structured and function in order to use them efficiently may include multiple data environments, cloud/AWS, primary and foreign key relationships, table design, database schemas, etc.Model Deployment: Understanding of: MDLC (Model Development Life Cycle), CI/CD/CT pipelines (using tools like Jenkins, CloudBees, Harness etc.), A/B testing. Pipeline frameworks like MLFlow, AWS SageMaker pipeline etc. model and data versioning.Statistics and Computing: Exceptional understanding of: Calculus, Multivariable Calculus, Linear Algebra, Differential Equations, Probability, Statistics, Applied Probability, Applied Statistics, Computer Science (Programming Methodologies), and Cloud. Knowledge of statistical techniques such as the use of descriptive, inferential, Bayesian statistics, time series analysis etc. to extract business insights and experimentation to solve business problemsData Wrangling: Preparing data for further analysis; Redefining and mapping raw data to generate insights; Processing of large datasets (structured, unstructured).Machine Learning: Understanding of machine learning theory, including the mathematics underlying machine learning algorithms. Expertise in the application of machine learning theory to building, training, testing, and monitoring machine learning models. Understanding and expertise in NLP (natural language processing).Programming Languages: Python, R, SQL, Java or Scala, SQL, Cypher 1 - 3 years of hands-on experience is required.Payrate: 55 - 63 / hr depending on experience.