Financial Data Analyst

1 month ago

Charlotte, United States Robert Half Full time
Job DescriptionJob Description

We are recruiting for a Data Scientist to join our team in the Financial Services industry, based in Charlotte, North Carolina. As a Data Scientist, you will be responsible for implementing data cleansing and transformation processes, performing exploratory data analysis, and applying machine learning algorithms to develop predictive models. This role offers a contract to hire employment opportunity.


Responsibilities:


-Required

Experience in Financial Services, some experience in Fraud or AML along with strong Python and SQL.


• Implement data cleansing and transformation processes using SQL, Python, and Alteryx to ensure data quality and readiness for analysis.

• Perform Exploratory Data Analysis (EDA) using Python libraries (Pandas, NumPy, Seaborn) to uncover trends, patterns, and anomalies in data.

• Utilize Python Label Encoder, and OneHotEncoder methods for categorical variable analysis.

• Enhance predictive accuracy by developing and fine-tuning models using Python and Spark.

• Apply machine learning algorithms such as decision trees, SVM, random forest to develop predictive models for various business applications including fraud detection and customer segmentation.

• Analyze massive datasets using artificial intelligence (AI) to provide insights into reducing risks, enhancing decision-making efficiency, and optimizing lending practices.

• Conduct internal audits and data analysis to ensure compliance and efficiency.

• Utilize data visualization techniques to present complex data in a comprehensible manner.

• Leverage extensive knowledge of SQL to answer complex queries and maintain databases.

• Utilize advanced analytics skills to drive data-driven decision making.

• Proficiency in Microsoft SQL and Python programming languages.
• Demonstrated understanding and application of data mining techniques.
• Experience in auditing within the financial services industry.
• Knowledge and practical application of data science concepts.
• Familiarity with Anti Money Laundering (AML) regulations and procedures.
• Ability to analyze complex financial data and draw meaningful conclusions.
• Strong communication skills to effectively relay insights from data analysis.
• Detail-oriented and capable of maintaining high accuracy in work.
• Proven ability to handle sensitive and confidential information.
• Bachelor's degree in Finance, Economics, or a related field.
• Professional certification in data analysis or a related field is preferred.
• Ability to work collaboratively as part of a team.
• Strong problem-solving skills and analytical thinking.
• Flexibility to adapt to changing business needs and deadlines.

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