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Science Leadership Jobs (NOW HIRING)

Merck Group

Head of Science Operations

Billerica, MA · On-site

Reporting directly to the head of AIDD, this is a senior scientific leadership role with direct responsibility for a team of medicinal and synthetic chemists, biologists, and automation scientists.

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Science Leadership information

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$80.5K

$111.9K

$144K

How much do science leadership jobs pay per year?

As of Jul 23, 2026, the average yearly pay for science leadership in the United States is $111,876.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,000.00 and $125,000.00 per year, depending on experience, location, and employer.

What can I do with a Masters of science in leadership?

A Masters of Science in Leadership prepares individuals for management roles across various industries, including science, healthcare, and technology. Graduates can pursue positions such as project manager, team leader, or department head, often requiring strong communication, strategic planning, and organizational skills. The degree can also support advancement into executive or administrative roles, especially when combined with relevant experience or certifications.

What does a science lead do?

A science lead oversees scientific projects, guides research teams, and ensures the accuracy and quality of scientific work. They often coordinate experiments, analyze data, and communicate findings to stakeholders, requiring strong leadership, technical expertise, and knowledge of scientific tools and methodologies.

What is the highest paid job in science?

In science leadership, executive roles such as Chief Scientific Officer or Vice President of Research tend to be the highest paid, often earning six-figure salaries or more. These positions require extensive experience, advanced degrees, and strong management skills, and they typically oversee research strategies and scientific teams within organizations.

What are some common challenges faced by professionals in Science Leadership roles, and how can they be effectively managed?

Professionals in Science Leadership roles often encounter challenges such as balancing administrative duties with scientific research, managing interdisciplinary teams, and ensuring clear communication across departments. Navigating conflicting priorities and fostering an environment that encourages innovation while maintaining project timelines are also frequent hurdles. These challenges can be effectively managed by developing strong organizational skills, delegating responsibilities appropriately, and promoting open, transparent communication within the team. Additionally, ongoing leadership training and mentorship can help cultivate the skills needed to address both scientific and managerial aspects of the role.

What is science leadership?

Science leadership refers to the roles and responsibilities of individuals who guide scientific research, innovation, and policy within organizations or institutions. Science leaders often direct research teams, manage projects, secure funding, and help set scientific priorities. They play a key role in fostering collaboration, mentoring junior scientists, and ensuring ethical standards. Effective science leaders also communicate scientific findings to stakeholders and the public, influencing the direction of scientific advancement.

What jobs will be left by 2030?

By 2030, roles in science leadership such as research directors, project managers, and science policy advisors are expected to remain in demand due to ongoing need for expertise in scientific innovation and management. However, automation and AI tools may reduce demand for routine administrative or data entry positions within scientific organizations. Strong leadership, communication, and technical skills will be essential for these roles to adapt to evolving technologies.

What is the difference between Science Leadership vs Research Scientist?

AspectScience LeadershipResearch Scientist
Required CredentialsAdvanced degrees (PhD), leadership experienceTypically PhD or Master's, specialized research skills
Work EnvironmentManagement, strategic planning, team oversightLaboratory or field research, data analysis
Employer & Industry UsageResearch institutions, biotech, pharma, academiaUniversities, research labs, industry R&D
Common Search & ComparisonLeadership roles in scienceHands-on research roles

Science Leadership involves managing teams, setting research strategies, and overseeing projects, often requiring leadership experience and advanced degrees. Research Scientists focus on conducting experiments, analyzing data, and advancing scientific knowledge through hands-on research. While both roles are integral to scientific progress, Science Leadership emphasizes management and strategic planning, whereas Research Scientists concentrate on experimental work.

What are the key skills and qualifications needed to thrive in Science Leadership, and why are they important?

To thrive in Science Leadership, you need a strong background in a scientific discipline, experience in research management, and often an advanced degree such as a PhD. Familiarity with data analysis software, project management tools, and grant-writing systems is typically required. Exceptional communication, strategic thinking, and team-building abilities set outstanding science leaders apart. These competencies enable effective guidance of research teams, secure funding, and foster innovation in scientific organizations.
More about Science Leadership jobs
What cities are hiring for Science Leadership jobs? Cities with the most Science Leadership job openings:
What states have the most Science Leadership jobs? States with the most job openings for Science Leadership jobs include:
What job categories do people searching Science Leadership jobs look for? The top searched job categories for Science Leadership jobs are:
Science Leadership jobs near you
Infographic showing various Science Leadership job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $111,876 per year, or $53.8 per hour.
Systems Architect - Data Science & Advanced Analytics

Systems Architect - Data Science & Advanced Analytics

Analytica

Bethesda, MD • On-site

$68 - $87.50/hr

Full-time

Medical, Retirement

Posted 11 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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