Data Scientist - Finance

Job Summary

The Data Scientist is critically impactful role to generate the deep and insightful analysis to support Teradata’ growth. This candidate will be responsible for analyzing financial data, developing predictive models, and communicating findings and insights to stakeholders. The ideal candidate must be a self-starter with a passion for solving complex problems and providing data-driven recommendations.

Essential Functions:
Conduct complex data analysis on financial data to derive actionable insights that inform business strategy and decision-making.

Develop predictive models to forecast financial performance and identify potential risks or opportunities.

Design and implement statistical models to support financial risk assessment and portfolio management.

Identify and integrate relevant external data sources into the company's data analytics framework to support financial forecasting and risk management.

Create visualizations and reports that communicate data-driven insights to stakeholders.

Collaborate with business partners to understand their analytical needs and develop solutions to address them.

Stay up to date with developments in financial data analytics and leverage emerging tools and techniques to drive innovation and improve processes.

Provide technical guidance and mentorship to junior team members.

Qualifications:
Master's or PhD in a quantitative field such as statistics, mathematics, physics, engineering, or computer science.

5+ years of experience in data analysis and modeling with a focus on financial data.

Experience with statistical programming languages such as R or Python.

Familiarity with financial data and concepts such as financial statements, ratios, and metrics.

Experience with data visualization tools such as Tableau, Power BI, or D3.js.

Excellent problem-solving and analytical skills.

Strong communication and collaboration skills.

Experience leading and mentoring junior team members.

Demonstrated ability to build effective cross-functional relationships.

Excellent reporting, analytical and modelling skills with ability to clearly summarize and present findings to achieve business objectives and goals.

Preferred Qualifications:
Experience with machine learning and deep learning algorithms.

Knowledge of financial regulations and compliance requirements.

Experience with cloud computing platforms such as AWS, Azure, Google Cloud.

Experience with SQL and database management systems.

Professional certifications such as CFA, FRM, or PRMIA.