Data Scientist

About Victory Capital:

Victory Capital is a diversified global asset management firm and employs a next-generation business strategy that combines boutique investment qualities with the benefits of a fully integrated, centralized operating and distribution platform.

Victory Capital provides specialized investment strategies to institutions, intermediaries, retirement platforms and individual investors. With 11 autonomous Investment Franchises and a Solutions Business, Victory Capital offers a wide array of investment products and services, including mutual funds, ETFs, separately managed accounts, alternative investments, third-party ETF model strategies, collective investment trusts, private funds, a 529 Education Savings Plan and brokerage services.

Victory Capital is headquartered in San Antonio, Texas, with offices and investment professionals in the U.S. and around the world. To learn more please visit www.vcm.com or follow Victory Capital on Facebook, Twitter, and LinkedIn.

General Summary and Purpose:

Victory Capital Management is committed to leveraging data to drive strategic decisions and innovation. We are seeking a Data Scientist to join our expanding Data and Analytics team. The ideal candidate will have a strong background in artificial intelligence, machine learning, data mining, and information retrieval to design, prototype, and build advanced analytics engines and services. You will collaborate with the broader team to implement machine learning algorithms that support our business units, design data experiments, and develop efficient models that drive revenue and enhance our decision-making processes.

You will report to the Data Science Manager and play a key role in transforming our data initiatives while working independently on projects from conception to deployment.

You Will:

• Identify appropriate uses of machine learning and use open source and AWS packages (including pandas, scikit-learn, and SageMaker) to write and deploy models to solve business problems.
• Demonstrate strong analytical problem-solving skills to translate ambiguous business questions into data science solutions.
• Own projects end-to-end, from problem definition through deployment and monitoring.
• Collaborate with team members to develop novel solutions using cutting-edge techniques and tools in our git-based workflow.
• Communicate complex technical concepts to non-technical stakeholders and explain the analytics approach and its benefits.
• Advocate and educate on the value of data-driven decision-making across the organization.
• Integrate analytical approaches into applications and tools with cross-functional teams.
• Develop scalable, interpretable models incorporated into data products.
• Engineer features by combining diverse data sources and transforming datasets.
• Share your passion for Data Science within the broader enterprise community and contribute to developing long-term processes and standards.
• Stay connected with external sources of ideas through conferences and community engagements.

You Have:

• 1-4 years of hands-on modeling experience required.
• Bachelor's degree in Computer Science, Engineering, Statistics, Information Technology, Informatics, or a related field.
• Proficiency in Python (working with DataFrames, pandas) and SQL.
• Experience working in an Agile team environment with git version control.
• Hands-on experience with hypothesis testing and machine learning for solving clustering, classification, regression, anomaly detection, simulation, or optimization problems on large datasets.
• Ability to clean, merge, and transform datasets to create new features.
• Experience with developing models on AWS or other cloud platforms (particularly AWS SageMaker).
• Experience in the deployment, monitoring, maintenance, and enhancement of models.
• Proficiency with data visualization tools such as PowerBI, Plotly, Seaborn, or Matplotlib.
• Excellent communication skills to explain complex technical concepts to non-technical stakeholders.
• Strong collaboration skills and ability to work effectively in a small team environment.
• Demonstrated ability to work independently and manage multiple projects simultaneously.

Additional Qualifications:

• Master’s or Ph.D. in a quantitative field such as Data Science, Statistics, Mathematics, Computer Science, or a related discipline.
• Experience with Generative AI technologies (e.g., LangChain, LLMs, AWS Bedrock) to develop and implement advanced AI applications.
• Experience with NLP techniques and libraries such as spaCy, NLTK, or BERT for text analysis and processing.
• Experience in building and deploying recommender systems.
• Expertise in financial modeling, financial services, or the investment management industry.
• Proficiency in advanced statistical techniques such as Bayesian inference, time series analysis, or survival analysis.
• Relevant certifications such as AWS Certified Machine Learning, TensorFlow Developer Certificate, or other recognized industry credentials.
• Proven track record of developing innovative solutions to complex data problems.

Our Benefits:

Victory Capital Management offers excellent Medical, Dental, Vision plans, Flexible PTO, Family Medical and Disability Leaves, Education Tuition Reimbursement and a 401k plan with a generous employer match.

Target Compensation:

The target base salary range for this position is $93,500 - $ 110,000.

Salaries are determined based on internal equity, internal salary ranges, market data/ranges, applicant’s skills and prior relevant experience, certain degrees, and certifications.

Victory Capital Management operates a pay-for-performance compensation philosophy and total compensation may vary based on role, location, department and individual performance.

Victory Capital Management’s total compensation package includes the opportunity for annual compensation bonuses and/or commissions and a generous benefits package.

We are committed to equal employment opportunity without regard to actual or perceived race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth, pregnancy-related conditions, and lactation), gender identity or expression (including transgender status), sexual orientation, marital status, military service and veteran status, physical or mental disability, genetic information, height, weight, hair texture or a hairstyle historically associated with race to include braids, locks, or twists; or any other characteristic protected by applicable federal, state, or local laws and ordinances.