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Truist · 16 hours ago

Data Scientist I

Greenville, SC

Full-time

Onsite

New Grad, Entry Level

0+ years exp

Truist is a financial services company seeking a Data Scientist I to perform sophisticated analytics to provide actionable insights that improve business outcomes. The role involves independently conducting data analytics, producing data visualizations, and engaging with stakeholders to identify business objectives.

BankingFinanceFinancial Services

No H1B

Responsibilities

Independently perform sophisticated data analytics (ranging from classical econometrics to machine learning, neural networks, and natural language processing) in a variety of environments using structured and unstructured data

Produce compelling data visualizations to communicate insights and influence outcomes among a wide array of stakeholders

Take accountability and ownership of end-to-end data science solution design, technical delivery, and measurable business outcome

Engage in stakeholder meetings to identify business objectives and scope solution requirements

With minimal guidance, write, document, and deploy custom code in a variety of environments (Python, SAS, R, etc.) to create predictive analytics applications

Use, maintain, share and collaborate through Truist internal code repositories to foster continual learning and cross-pollination of skillsets

Actively research and advocate adoption of emerging methods and technologies in the data science field, with the eye of continually advancing Truist’s capabilities

Exercise sound judgment and fosters risk management culture throughout design, development, and deployment practices; partner with cross-functional teams to coordinate rules on data usage, data governance and analytics capabilities

Qualification

Statistical methodsData cleansing methodologiesData extraction (SQL)Machine learningHadoopPythonData visualizationCollaborationProblem-solvingCommunication

Required

Bachelor's degree and zero to four or more years of experience in a quantitative field such as Finance, Mathematics, Analytics, Data Science, Computer Science, or Engineering, or equivalent education and related training

Exhibit understanding of statistical methods, including a broad understanding of classical statistics, probability theory, econometrics, time-series, and primary statistical tests

Familiarity with linear algebra concepts for optimization, complex matrix operations, eigenvalue decompositions, and principal components; working knowledge of calculus/differential equations, with understanding of stochastic processes

Demonstrate understanding of data cleansing and preparation methodologies, including regex, filtering, indexing, interpolation, and outlier treatment

Strong familiarity with data extraction in a variety of environments (SQL, JQuery, etc.)

Working knowledge of Hadoop, Pig, Hive, and/or NoSQL, Spark

Experience in managing multiple projects with tight deadlines in a collaborative environment