The disciplines of data science and finance work to create effective organizations and profitable businesses. Recent advancements in data science are transforming the financial sector, as artificial intelligence and other data-driven innovations make it easier than ever to analyze and act on financial insights.
There has never been a better time to start a career in this field, as evolutions in the sector often create new, specialized job opportunities. Below, we examine the benefits of incorporating data science into finance and how careers in the industry can benefit from both disciplines.
With the myriad amounts of data that go into a financial plan, a bank’s vast accounts, and the overall stock market, there’s something to be said for efficient, reliable forms of collecting and interpreting data. Data science enhances reliability and efficiency in the financial sector.
Machine learning and data analytics provide predictive analytics, enabling companies to anticipate risks, including loan defaults and fraud. This can save thousands of dollars and protect a company’s reputation and image with its customers. Big data analytics can also enhance credit scoring models, helping individuals understand their financial situation and companies assess risk when giving loans.
Fraud detection machine learning algorithms can identify suspicious patterns and flag fraudulent transactions, giving customers of a financial institution peace of mind as they spend money.
Data analysis can help companies segment their customers based on behavior and needs, informing targeted marketing, assistance, and personalized offers. The real-time analysis provided by big data enables professionals to assess and analyze customer behavior in real-time, allowing businesses to make informed decisions and provide timely, relevant recommendations.
Another feature of data in finance comes through customer sentiment analysis. Through this data, companies can analyze social media, news, and the current financial landscape to gauge customer sentiment and understand trends, allowing them to prepare services and responses for their customers in advance.
Data analytics also provides valuable insights into algorithmic trading, helping financial institutions to implement data science systems that automate trades based on collected market data and predefined rules and insights. This can mitigate the guesswork associated with investing and trading, freeing professionals up for more strategic tasks and allowing them more time to build relationships with their clients.
This information also allows professionals to optimize their prices. As the market changes and supply and demand fluctuate, professionals can change their prices to meet current customer demand and to match the value of their expertise.
Data analytics provides evidence and examples of whether professionals observe best practices throughout all steps of the financial process. This information helps professionals monitor transactions safely and efficiently, including the implementation of AI in an ethical manner.
Numerous career options in data science and finance exist, each with varying levels of experience and corresponding salary differences.
Financial data scientists are skilled professionals who provide support and advice to the relevant teams within an organization. They develop tools and dashboards to improve the investment process. Utilizing data sets and coding rules to decipher patterns and insights from information, they use this information to make recommendations to their clients about their investments.
Financial data scientists typically make anywhere from $113,000 to $175,000 a year.
Data engineers working in finance build and maintain data pipelines, ensuring the creation of clean, well-organized, and accessible data. They analyze large financial datasets, helping bring actionable insights out of large amounts of data and inform their clients of the best course of action when faced with new financial information.
Financial data engineers typically make around $129,716 a year.
Risk managers use data and analytics to assess and monitor financial risks. Their work involves assessing potential threats to a company’s assets or earning capacity. They analyze and predict these risks, enabling companies to develop effective strategies for managing or mitigating them. Threats to profitability include market volatility, credit risk, liquidity risk, and operational risk.
Financial risk managers earn an average annual salary of $124,026.
Quantitative analysts in finance apply mathematical and statistical methods to financial and risk management problems. They work with data to develop complex models that predict market trends and investment risks, leading to more secure businesses. They can also manage individual portfolios and assist their clients in making informed investment decisions.
QUANT professionals have varied salaries depending on the area of finance in which they work.
When working in finance, having the proper training and certifications matters. It’s a lucrative industry, but you must first invest in your education and experience. Here are the basic steps to enter this industry:
Develop Your Practical Skills: Get comfortable with coding, quantitative and qualitative analysis, machine learning, data visualization, and your people skills. Each of these competencies will make you a stronger financial professional and more marketable in a competitive industry.
Specialize and Network: Focus on finance and specialize your knowledge in this field, staying current with the ever-changing financial industry. Consider pursuing certifications in a specific area of finance to enhance your expertise and demonstrate your proficiency in that field.
Obtain the Right Degree: Pursuing a graduate degree in a financial discipline develops practical skills and establishes credibility in the field. Whether you choose to pursue a master’s degree in finance or a more specialized degree like a degree in financial planning or accounting, it’s worth it to invest in your education.
At the University of Dallas, we offer several graduate degrees rooted in finance and data science, preparing well-versed and virtuous leaders for the future of finance.
The Master of Science in Data Science and Artificial Intelligence is a 36-hour program designed to prepare students with advanced technical and analytical expertise. Graduates gain the ability to:
With training in artificial intelligence, graduates stand out in today’s technical and data-driven world.
Read more about the value of earning a degree in data science and AI in our blog, Examining ROI: Is a Master's in Data Science and AI Worth It?
The Master of Science in Business Analytics is a STEM-designated, 30-credit-hour program aimed at equipping students with the technical skills to derive meaning from big data and to communicate results to key stakeholders effectively. In the master’s in business analytics programs, students emerge with the skills to:
Learn more in our blog, Business Analytics vs Data Science: Key Differences.
The Master of Science in Financial Planning is a 30-credit-hour program designed to prepare students for success in one of today’s most in-demand fields. To equip students with emerging tools, this degree includes financial analytics, modeling, and AI tools in the curriculum. The program equips graduates with:
The Master of Science in Finance provides professionals with an intensive education in one of today’s most technical and versatile fields. This degree prepares students for CFA exams, investment banking, asset management, and data-driven financial analytics roles. The program equips graduates with:
Graduates are well prepared for careers in investment, security analysis and portfolio management, corporate financial management, and financial advising. Students may also pursue a concentration in data science and artificial intelligence, integrating financial analytics, modeling, and AI tools into their courses and preparing them as marketable professionals in their field.
Courses in this program align with the CFA's curriculum enhancements, preparing students with the same in-demand skills emphasized by the CFA, including:
The Master of Science in Accounting provides accounting professionals with the advanced preparation needed to thrive in today’s financial environment. The program equips graduates with:
By choosing any of these graduate degrees from the University of Dallas, you will invest in a career that impacts multiple industries and provides countless opportunities for job growth and professional impact. To learn more about our finance degrees and how the University of Dallas shapes professionals for the future of finance, download our resource.
You can also schedule a meeting with one of our advisors to learn more about our programs. Ready to start your journey in finance and data? Apply today.