Senior Data Science Analyst - Boston, United States - MFS Investment Management

Description

Senior Data Science Analyst (Massachusetts Financial Services Co.; Boston MA):

The Senior Data Science Analyst, in collaboration with the business strategist team, will analyze and evaluate large quantities of data. Leveraging advanced data analysis skills, the Senior Data Science Analyst will create, develop, and iterate innovative approaches to answer business questions. This individual will apply a data-driven analytical approach to a variety of problems related to the Compliance team. The individual in this role will be responsible for the entire analytical process - from data preparation to solution outlining to implementation and interpretation of results. The Senior Data Science Analyst will constructively discuss findings in dialogue with business strategists and senior leaders. Duties include: Working with the Business strategists, information technology and operations to integrate business needs with data analytics solutions; Identifying and preparing the data (from internal and external sources); Building models using advanced analytical techniques. This will include descriptive, prescriptive and other advanced analytical techniques; and Working with cross-functional stakeholders and leaders to gather and synthesize relevant data, analyzing and developing final recommendations. Hybrid telecommuting permitted pursuant to company policy.

Minimum Requirements:

Masters degree in Computer Science, Statistics, Mathematics, Business Analytics, or a related discipline, plus one year of relevant work experience in an analytics/data science role or related role pre- or post-Masters degree.

Must have:

Demonstrated experience with analyzing complex, high volume, high dimensionality data from varying sources and both structured and unstructured; Demonstrated ability to work collaboratively in a team environment and work effectively with people at all levels in the organization; Demonstrated ability to communicate complex ideas effectively, and willingness to understand the business implications of a wide variety of data; Demonstrated advanced knowledge of machine learning/statistical techniques, such as data mining, regression, decision trees, text mining; Knowledge of Gradient boosting, random forest, deep learning/AI; and Proficiency in Python, SQL, R and/or SAS. (Unless otherwise indicated, employer is seeking the ability in the skills listed above with no specific number of years of experience required. All experience can be gained concurrently.)

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