Data Scientists 2

Key Skills

Java Programming, Microsoft Office suites, Python Programming, SQL, Azure, Big Data Technology, Scala Programming, Machine learning techniques, Data Analytics, R Programming, PySpark, Effective communication skills

Job Description

The Data Scientist 2 uses mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions. The Data Scientist 2 work assignments are varied and frequently require interpretation and independent determination of the appropriate courses of action.

Responsibilities

The Data Scientist uses mathematics, statistics, machine learning, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions. The Data Scientists’ work assignments involve moderately complex to complex issues where the analysis of situations and data requires an in-depth evaluation of variable factors. The Data Scientist uses machine learning and artificial intelligence to develop sophisticated models, using both structured and unstructured data sets for analysis.

As a Data Scientist, you will:

• Use techniques from supervised and unsupervised machine learning, statistical analysis, Or predictive modeling to deliver business insights to prospects and customers
• Work directly with customers to educate them on “moving beyond BI” and training their internal resources to execute advanced forms of analytics
• Create reusable implementations of statistical tests and models using the available technologies in the ecosystem
• Work with the academic and business community to develop new techniques and to contribute to research in the area of advanced analytics on large databases
• Generate new product requirements for the engineering group to enhance the analytics capabilities of the database
• Assist in customer engagement management, requirements definition, project scoping, timeline management, and results documentation to ensure professional relationship management
• Use machine learning techniques to assess outcomes of interventions, clinical programs or marketing campaigns
• Build ‘smart’ systems that learn from health intervention outcomes over time

Required Qualifications

• Master’s Degree in Math, Computer Science, Analytics, Quantitative Social Sciences or related analytical field
• 2 years’ technical experience
• Experience working with and analyzing various types of data using R, Python or similar software
• Experience in using mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions
• Experience using machine learning techniques such as neural networks, random forest, gradient boosting, etc.
• Naturally curious and comfortable with ambiguity
• Demonstrated strategic and analytical thinking
• Clear and concise oral and written communication skills, with a proven ability to translate complex methodologies and analytical results to higher-level business insights and key takeaways
• Strong interpersonal and consulting skills

Preferred Qualifications

• PhD Degree in Math, Computer Science, Analytics, Quantitative Social Sciences or a related field
• 3+ years’ technical experience
• Experience in Big Data environment specifically PySpark, Scala, or Microsoft Azure
• Previously applied machine learning to help a firm reach objectives
• Work experience in a health care and/or Insurance setting

Additional Information

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