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Computer Science Data Science Jobs in Maryland (NOW HIRING)

Education: Bachelor's degree in data science, computer science, statistics, mathematics, engineering, operations research, information systems, analytics, or a related technical field. Advanced ...

Education: Bachelor's degree in data science, computer science, statistics, mathematics, engineering, operations research, information systems, analytics, or a related technical field. Advanced ...

Education: Bachelor's degree in data science, computer science, statistics, mathematics, engineering, operations research, information systems, analytics, or a related technical field. Advanced ...

Master's degree in Computer Science, Electronics Engineering, or other engineering or technical discipline is required OR * 8 years of relevant experience in data science, data engineering, or ...

New

Required : • Bachelor's Degree Data Science, Computer Science, Statistics, Mathematics, Economics, or related field required or equivalent years of experience • 7-10 years Experience in data ...

Data Scientist

Annapolis, MD · On-site

$119K - $285K/yr

Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge. Through analytic modeling, statistical analysis ...

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Computer Science Data Science information

See Maryland salary details

$36.4K

$119.1K

$190.7K

How much do computer science data science jobs pay per year?

As of Jul 30, 2026, the average yearly pay for computer science data science in Maryland is $119,123.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,600.00 and $132,000.00 per year, depending on experience, location, and employer.

Is data science high paying?

Data science roles, including those in computer science and data science, are generally high paying due to the specialized skills required, such as programming, statistical analysis, and machine learning. Salaries tend to be above average compared to many other tech positions and often increase with experience, certifications, and advanced skills in tools like Python, R, and SQL.

Is 40 too late for data science?

Computer Science Data Science is a field where individuals can enter at any age, including 40, as long as they develop relevant skills such as programming, statistics, and machine learning. Many professionals successfully transition into data science later in their careers by gaining certifications, building portfolios, and gaining practical experience.

Can computer science majors get data science jobs?

Yes, computer science majors often qualify for data science roles because they typically have strong programming, statistical, and analytical skills. Success in obtaining a data science job may also depend on experience with tools like Python, R, and SQL, as well as knowledge of machine learning and data visualization. Additional certifications or projects can enhance employability in this field.

Will AI replace data science?

AI is transforming data science by automating tasks like data analysis and model development, but it is unlikely to fully replace data scientists. Instead, data scientists will increasingly focus on interpreting AI outputs, developing new algorithms, and applying domain expertise. Skills in programming, statistical analysis, and machine learning tools remain essential for the role.
What are popular job titles related to Computer Science Data Science jobs in Maryland? For Computer Science Data Science jobs in Maryland, the most frequently searched job titles are:
What job categories do people searching Computer Science Data Science jobs in Maryland look for? The top searched job categories for Computer Science Data Science jobs in Maryland are:
What cities in Maryland are hiring for Computer Science Data Science jobs? Cities in Maryland with the most Computer Science Data Science job openings:
Infographic showing various Computer Science Data Science job openings in Maryland as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 15% Part Time, and 4% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $119,123 per year, or $57.3 per hour.

Systems Architect - Data Science & Advanced Analytics

Analytica

Bethesda, MD • On-site

$68 - $87.50/hr

Full-time

Medical, Retirement

Re-posted 19 days ago


Job description

Analytica is seeking a Systems Architect – Data Science & Advanced Analytics to provide strategic and technical leadership in designing, implementing, and modernizing enterprise data and advanced analytics solutions. This role serves as the lead architect for data science initiatives, responsible for developing scalable analytics environments, machine learning solutions, and enterprise data architectures with a strong emphasis on Databricks, Apache Spark, and modern cloud-based data platforms.
The ideal candidate will work closely with data scientists, data engineers, business stakeholders, and technical leadership to develop innovative analytics solutions that transform complex data into actionable insights. This individual will provide technical vision, establish best practices, and lead the adoption of advanced analytics and machine learning capabilities across the organization.

Analytica has been recognized by Inc. Magazine as a fastest-growing private US small business.  We work with U.S. government customers in health, civilian, and national security missions.  Analytica offers competitive compensation with opportunities for bonuses, employer paid health care, training and development funds, and 401k match.  

 
Key Responsibilities
Data Science Leadership

  • Serve as the Lead Architect for enterprise Data Science and Advanced Analytics initiatives.
  • Develop and drive the organization's vision and strategy for Big Data, Artificial Intelligence, and Machine Learning solutions.
  • Lead the design and implementation of scalable data science environments that support experimentation, model development, validation, and deployment.
  • Provide technical leadership and mentorship to Data Scientists, Machine Learning Engineers, and Analytics teams.
  • Identify emerging technologies and analytical methodologies that improve organizational capabilities and mission outcomes.
Advanced Analytics & Machine Learning
  • Architect end-to-end machine learning and advanced analytics solutions using modern data platforms and distributed computing frameworks.
  • Design scalable workflows for data preparation, feature engineering, model training, evaluation, and production deployment.
  • Collaborate with cross-functional teams to translate business and mission objectives into advanced analytical solutions.
  • Guide the development of predictive models, statistical analyses, optimization models, and AI-driven decision support tools.
  • Establish best practices for model governance, reproducibility, documentation, and performance monitoring.
Data Architecture & Big Data Solutions
  • Design enterprise data architectures that enable large-scale analytics and machine learning workloads.
  • Lead the development of data pipelines and analytical frameworks utilizing Databricks Lakehouse architecture, Delta Lake, and Apache Spark.
  • Ensure data solutions are scalable, reliable, high-performing, and aligned with enterprise architecture standards.
  • Architect integrated data ecosystems that support structured, semi-structured, and unstructured data sources.
  • Lead modernization initiatives that enhance data accessibility, analytical capabilities, and operational efficiency.
Strategic Collaboration
  • Partner with executive leadership and business stakeholders to define data and analytics roadmaps.
  • Translate complex technical concepts into business-focused recommendations and strategic initiatives.
  • Lead architecture reviews and provide expert guidance on enterprise analytics solutions.
  • Foster collaboration between Data Science, Data Engineering, and business teams to deliver high-impact analytical products.

Required Qualifications
Experience
  • Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, or a related technical discipline (Master's preferred).
  • 10+ years of progressive experience designing and implementing advanced analytics, machine learning, or Big Data solutions.
  • Demonstrated experience serving as a technical lead or subject matter expert for enterprise data science initiatives.
  • Experience leading technical teams and architecting large-scale analytics platforms.
  • Experience architecting enterprise-scale data science and advanced analytics platforms.
  • Experience developing AI/ML solutions supporting mission-critical or large-scale business operations.
  • Knowledge of modern data governance and responsible AI principles.
  • Experience with experimentation frameworks, model operationalization, and analytical product development.
  • Familiarity with Agile product development and collaborative data science workflows.
Required Technical Skills
Data Science & Machine Learning
  • Machine Learning model development and lifecycle management
  • Statistical analysis and predictive modeling
  • Artificial Intelligence and Advanced Analytics methodologies
  • Feature engineering and model evaluation techniques
  • Data exploration and analytical solution design
Big Data & Data Engineering
  • Databricks Lakehouse Platform
  • Apache Spark
  • Delta Lake
  • Distributed data processing frameworks
  • ETL/ELT and modern data pipeline architectures
  • Data modeling and enterprise data architecture
Analytics & Visualization
  • Advanced analytics solution design
  • Business Intelligence and data visualization concepts
  • Dashboard and reporting architecture
  • Data storytelling and insight generation
Leadership
  • Technical strategy development
  • Enterprise architecture governance
  • Cross-functional team leadership
  • Stakeholder engagement and executive communication
  • Mentoring and coaching technical teams
Certifications:
Candidates should possess one or more of the following certifications:
Databricks
  • Databricks Certified Professional Data Scientist
  • Databricks Certified Professional Data Engineer
  • Databricks Certified Machine Learning Associate
  • Databricks Certified Developer for Apache Spark
Big Data & Analytics
  • Apache Spark or Big Data certifications
  • Tableau Certified Professional (Desktop or Server)
  • Other industry-recognized data science, analytics, or visualization certifications
About Analytica: Analytica is a leading consulting and information technology solutions provider to public sector organizations supporting health, civilian, and national security missions. The company is an award-winning SBA certified 8(a) small business that has been recognized by Inc. Magazine each of the past three years as one of the 250 fastest-growing companies in the U.S. Analytica specializes in providing software and systems engineering, information management, analytics & visualization, agile project management, and management consulting services. The company is appraised by the Software Engineering Institute (SEI) at CMMI® Maturity Level 3 and is an ISO 9001:2008 certified provider.

Analytica LLC is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all individuals, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other characteristic protected by applicable federal, state, or local law. As a federal contractor, we comply with the Vietnam Era Veterans' Readjustment Assistance Act (VEVRAA) and take affirmative action to employ and advance in employment qualified protected veterans. We ensure that all employment decisions are based on merit, qualifications, and business needs. We prohibit discrimination and harassment of any kind. Analytica LLC also provides reasonable accommodations to applicants and employees with disabilities, in accordance with applicable law.

To enhance efficiency, fairness, and accuracy, Analytica may use AI-assisted tools to support certain aspects of our hiring process.

  • Application Review: AI tools may help identify skills and experiences relevant to the role.
  • Interview Support: AI-powered notetaking tools may be used during interviews to document discussions and summarize key points.

These tools are used to assist our team. All hiring decisions are made by Analytica recruiters and hiring managers.

By submitting an application, you acknowledge that AI-assisted tools may be used to support parts of the application and interview process.

When receiving email communication from Analytica, please ensure that the email domain is analytica.net to verify its authenticity.

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