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The Robinson Group is partnered with a two longstanding clients to fill critical, newly created Data Scientist roles.

Each are leaders in their respective industries and both are growing their data science organizations.

Our clients can offer transfer/sponsorship.

Our clients are open to some relocation assistance.

One role is in Cincinnati, OH and the other role is 100% remote.

The Data Scientist will drive the business by collecting and analyzing customer and operational data to deepen the understanding of the customer behavior across all channels.

• Apply a broad range of advance modeling techniques and theories from statistics, machine learning, heuristics, NLP and deep learning to create algorithms and predictive models that are actionable for the business
• Design, develop and program methods, processes, and systems to consolidate and analyze diverse “big data” sources to generate actionable insights
• Challenge the status quo and impact business outcomes
• Exercise judgment in selecting optimal AI/ML methods, techniques, and evaluation criteria for obtaining results
• Build robust DoE plans, testing plans, validation of models using unit test cases and/or other applicable testing
• Work directly with the business to understand their questions, business processes, programs and/or initiatives; then identify how analytical solutions could help deliver value
• Learn and understand insurance industry practices, standards, and concepts for all business lines to determine how they are interrelated and the impact on data integration
• Determine necessary data sets and translate data into viable insights and business recommendations
• Utilize software best practices in creating models, algorithms, and modern techniques
• Utilize research and problem-solving skills that include descriptive, predictive, and prescriptive analytics
• Understand data collection capability in business systems and recommend enhanced business processes
• Assist (in partnership with data architects) in automating data wrangling, iterative solution search and operationalization of models
• Provide analytical support and guidance across the enterprise, through database querying, third-party vendor reporting, and external partner reports
• Work with cross-functional teams to resolve data discrepancies and system issues
• Communicate with and present to managers from all levels of the business

Requirements

• Master’s degree or equivalent combination of education and experience required. Desired fields of education preferably in Data, Computer or Actuarial Sciences, Engineering, Statistics or Mathematics.
• 2+ years of relevant experience in the areas listed below, or equivalent combination of education and experience. Experience needs to include deep hands-on involvement in developing models and coding techniques.
• Experience programming in R, SQL, Python required.
• Working knowledge of statistical areas such as ANOVA, multiple regression, timeseries modeling, decision trees, clustering, Random Forest, Gradient boosting, and SVM required.
• Strong research, statistical, analytical, processing and mathematical skills with ability to structure, implement efficient coding, create/maintain predictive algorithms and conduct analysis is required.
• Experience building and deploying models in a Big Data environment; comfortable with using Hive, MapReduce, Spark SQL, PySpark, JavaScript, Sqoop desired.
• Working knowledge of any of the analytics platforms like SAS, MatLab, Data Robot, Alteryx, Dataiku, etc. is desired.
• Working knowledge of AIML packages such as Keras, Theano, TensorFlow is desired.
• Working knowledge of cloud infrastructures such as AWS or Azure desired.
• Experience coding and maintaining predictive algorithms desired.
• Knowledge of principal component analyses, deep learning using RNN/CNN, Hidden Markov, NLP, Bayesian techniques is desired.