Data Scientist- Contract to Hire- W2

Contract to hire position with a major financial firm.This position is hybrid to Newark, NJAs a Data Scientist on the Data Science team, you will partner with our diverseteam of Engineers, Economists, Computer Scientists, Mathematicians, Physicists,Statisticians and Actuaries tasked with mining our industry-leading internal data to developnew analytics capabilities for our businesses. The role requires a rare combination ofsophisticated analytical expertise; business acumen; strategic mindset; client relationshipskills, problem solving; and a passion for generating business impact. This is an excitingopportunity to be a part of a strategic initiative that is evolving and growing over time! Inaddition to applied experience, you will bring excellent problem solving, communicationand teamwork skills, along with agile ways of working, strong business insight, an inclusiveleadership demeanor and a continuous learning focus to all that you do.Here is what you can expect in a typical day:• Responsible for the hands-on development of sophisticated data science solutionscomprising the portfolio developed by the Lead Data Scientist and Actuaries and thetechnical requirements specified by the Lead Data Scientist and Actuaries.• Perform hands-on data analysis, model development, model training, modeltesting, model deployment.• Continuously research new methods for problem solution, including newalgorithms, modeling techniques, and data analytics techniques.• Write production-level code and partner with machine learning engineers to pushdevelopment code into production.• Partner with machine learning engineers to productionized machine learningmodels. Partner with data engineers to build data pipelines. Partner with softwareengineers to integrate solutions with business platforms.• Work closely with the business and data science lead to recommend and developmodels for GI financial underwriting, medical underwriting, marketing analytics andother business use cases.• Manage external vendors in the execution of the data science development process.The Skills and expertise you bring:• Advanced degree (Masters, Ph.D.) in Mathematics, Statistics, Engineering,Econometrics, Physics, Computer Science, Actuarial, Data Science, or comparablequantitative disciplines.• Working on complex problems in which analysis of situations or data requires an in[1]depth evaluation of various factors. Exercises judgment within broadly definedpractices and policies in selecting methods, techniques, and evaluation criteria forobtaining results.• Knowledge of business concepts, tools and processes that are needed for makingsound decisions in the context of the company's business. Create and testhypotheses for customer engagement and wellness programs.• Experience in research, designing experiments (ex: A/B testing), working with claimsand customer experience data. An insurance actuary background is preferred butnot required.• Ability to learn creative skills and knowledge on an on-going basis through self[1]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 sourcesusing 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 andfunction in order to use them e8iciently may include multiple data environments,cloud/AWS, primary and foreign key relationships, table design, database schemas,etc.o Knowledge of how to work with data from (do not build)o SQL skills (relational) - CORE / Initial Proficiencyo Unstructured (NoSQL)o Graph / ontology (DB Graph)• 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 dataversioning.• Statistics and Computing: Exceptional understanding of: Calculus, MultivariableCalculus, Linear Algebra, Di8erential Equations, Probability, Statistics, AppliedProbability, 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 insightsand experimentation to solve business problems• Data Wrangling: Preparing data for further analysis; Redefining and mapping rawdata to generate insights; Processing of large datasets (structured, unstructured).• Machine Learning: Understanding of machine learning theory, including themathematics underlying machine learning algorithms. Expertise in the applicationof machine learning theory to building, training, testing, and monitoring machinelearning models. Understanding and expertise in NLP (natural language processing).• Programming Languages: Python, R, SQL, Java or Scala, SQL, Cypher