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Machine Learning Finance Jobs in Baltimore, MD (NOW HIRING)

Work you'll do As a Finance Analytics & AI Manager on the Finance Transformation team, you'll work ... One or more certifications in artificial intelligence, machine learning, Amazon Web Services ...

Work you'll do As a Finance Analytics & AI Manager on the Finance Transformation team, you'll work ... One or more certifications in artificial intelligence, machine learning, Amazon Web Services ...

Minimum Years of Experience * 2 years' experience in finance, accounting, FP&A, or data analytics, preferably with exposure to AI/machine learning initiatives and revenue/expense management. Open to ...

They are seeking AI/ML Engineers to build, deploy, and maintain machine learning models and data ... project management and financial analysis. Founded in 2007, the company is headquartered in ...

Data Scientist

Annapolis Junction, MD · On-site

$100K - $280K/yr

In this role, you will work at the intersection of data analysis, machine learning, and mission ... Background in specific domains (e.g., marketing analytics, healthcare, finance). Clearance TS/SCI ...

Data Scientist 2

Annapolis, MD · On-site

$115K - $145K/yr

This role combines artificial intelligence and machine learning skills with a strong foundation in ... financial wellness, retirement planning, family assistance, continued education, and paid time off.

Showing results 21-40

Machine Learning Finance information

See Baltimore, MD salary details

$24.8K

$92K

$134.6K

How much do machine learning finance jobs pay per year?

As of Aug 10, 2026, the average yearly pay for machine learning finance in Baltimore, MD is $92,042.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,500.00 and $108,300.00 per year, depending on experience, location, and employer.

Can machine learning be used in finance?

Machine learning finance roles involve applying algorithms to analyze financial data, detect patterns, and make predictions for trading, risk management, and fraud detection. Professionals in this field often use tools like Python, R, and specialized libraries, and require strong statistical and programming skills. These applications improve decision-making and operational efficiency in financial institutions.

What are the key skills and qualifications needed to thrive in machine learning finance, and why are they important?

To excel in Machine Learning Finance, you need strong quantitative skills, proficiency in programming (typically Python or R), and a solid background in both finance and machine learning, often supported by a relevant degree such as in computer science, statistics, mathematics, or finance. Familiarity with machine learning libraries (like TensorFlow, scikit-learn), financial modeling tools, and certifications such as CFA or FRM can be highly beneficial. Excellent problem-solving abilities, communication skills, and a collaborative attitude help professionals translate complex data into practical financial insights and work effectively with both technical and non-technical stakeholders. These competencies enable you to create robust predictive models, drive innovation in financial analysis, and ensure sound decision-making in dynamic industry settings.

What are some typical challenges faced by professionals in machine learning finance roles?

Professionals in Machine Learning Finance often encounter challenges such as working with noisy or incomplete financial data, keeping up with rapidly evolving algorithms, and ensuring model compliance with industry regulations. They may also need to bridge the gap between technical model development and practical business needs, communicating complex findings to non-technical teams. These roles typically involve close collaboration with traders, financial analysts, and risk managers to ensure that machine learning solutions are both accurate and actionable. Facing these challenges can be rewarding, offering significant opportunities for skill development and career advancement in a data-driven financial landscape.

What is a machine learning finance?

A Machine Learning Finance job involves applying machine learning techniques to financial problems such as risk assessment, algorithmic trading, fraud detection, and portfolio optimization. Professionals in this field build predictive models, analyze large datasets, and automate decision-making processes to improve financial performance. They typically work with tools like Python, TensorFlow, and financial datasets to develop AI-driven solutions. These roles require expertise in machine learning, statistics, and financial markets, often blending data science with quantitative finance.

What are popular job titles related to Machine Learning Finance jobs in Baltimore, MD? For Machine Learning Finance jobs in Baltimore, MD, the most frequently searched job titles are:
Infographic showing various Machine Learning Finance job openings in Baltimore, MD as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $92,042 per year, or $44.3 per hour.

Pointer TechnologiesData Scientist

Pointer Technologies

Annapolis Junction, MD • On-site

Full-time

Re-posted 19 days ago


Job description

Job Summary:
Pointer Technologies is seeking a skilled and innovative Data Scientist to join our dynamic team. In this role, you will work at the intersection of data analysis, machine learning, and mission strategy to uncover insights, build predictive models, and help solve mission-critical problems.
Responsibilities:
• Analyze large, complex datasets to uncover patterns, trends, and insights.
• Develop predictive and prescriptive models to address key mission challenges.
• Build, test, and deploy machine learning models and algorithms.
• Collaborate with cross-functional teams to understand mission objectives and translate them into data-driven solutions.
• Communicate findings and recommendations effectively to both technical and non-technical stakeholders.
• Design and implement data visualization dashboards to support real-time decision-making.
• Research and stay updated on the latest advancements in data science and machine learning.
Qualifications:
Required:
• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.
• Proficiency in programming languages such as Python or R.
• Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, SciPy).
• Solid understanding of statistical methods, machine learning algorithms, and predictive modeling techniques.
• Familiarity with data visualization tools like Tableau, Power BI, or Plotly.
• Hands-on experience with SQL and working with large-scale databases.
• TS/SCI clearance with polygraph required
Preferred:
• Knowledge of cloud-based data platforms (e.g., AWS, Azure).
• Experience with big data technologies like Spark, Hadoop, or Databricks.
• Familiarity with MLOps workflows and tools.
• Strong mission familiarity and ability to frame data-driven insights in the context of organizational goals.
• Background in specific domains (e.g., marketing analytics, healthcare, finance).
Company:
Pointer Technologies provides mission specific software services aimed at solving our nations toughest technical problems. Founded in 2023, the company is headquartered in , , with a team of 11-50 employees. The company is currently Early Stage.