BSc Data Science

3 Years On Campus Bachelors Program

London School of Economics and Political Science

Program Overview

The BSc Data Science at the London School of Economics & Political Science (LSE) is a rigorous, mathematically grounded program designed for students passionate about data analytics, statistics, and programming. It equips graduates with the skills to thrive in data-driven roles across sectors like technology, finance, government, and research.


Curriculum Structure:

Year 1: Students begin with foundational courses in statistical theory (ST102), mathematical methods (MA100), and programming (ST101A). The curriculum also includes LSE100, a half-unit course exploring societal issues like climate change or AI ethics. This year establishes a strong base in data handling and analytical thinking.

Year 2: The focus shifts to advanced topics such as probability and distribution theory (ST206), applied regression (ST211), and further mathematical methods (MA222). Students also delve into algorithms and data structures (MA214) and databases (ST207), enhancing their technical proficiency. This stage deepens understanding and prepares for complex data challenges.

Year 3: The final year emphasizes independent research and specialization. Students undertake a dissertation, applying their accumulated knowledge to a significant data science problem. Elective courses allow for customization, enabling students to tailor their expertise to specific interests or career paths.


Focus Areas: Data analytics, machine learning, statistical modeling, programming, artificial intelligence, social science applications.

Learning Outcomes: Proficiency in data analysis workflows, statistical inference, machine learning algorithms, programming languages (e.g., Python), and application of data science in social contexts.

Professional Alignment: The program is accredited by the University of London and prepares students for careers in data science, analytics, and related fields.

Reputation: LSE is globally recognized for its excellence in social sciences and quantitative disciplines, consistently ranking among the top universities worldwide.


Embarking on the BSc Data Science at LSE offers a unique blend of rigorous academic training and practical application, positioning graduates for success in the evolving data landscape.

Experiential Learning (Research, Projects, Internships etc.)

Embarking on the BSc Data Science at the London School of Economics & Political Science (LSE) goes beyond learning theory—it places you in a vibrant environment where data science meets real-world challenges. Through practical experiences, industry engagement, and collaborative projects, you’ll build the hands-on skills needed to thrive in the fast-evolving world of data science.

The program is anchored by the Data Science Institute (DSI), a hub for interdisciplinary learning and research. This connection ensures that you not only master core data science concepts but also learn how to apply them in social science and policy contexts.

Experiential Learning Opportunities:

Field Trips to Industry Leaders: Explore how data science works in practice through visits to leading organizations such as Google, the Bank of England, and the Cabinet Office. These trips offer firsthand exposure to the role of data in shaping industries and policies.

Specialized Modules by the DSI: Select from four advanced data science modules designed to deepen your knowledge and expand your perspective, equipping you with skills relevant to both research and professional practice.

Collaborative Projects and Seminars: Join interactive seminars and workshops that encourage teamwork with peers and experts, helping you strengthen your problem-solving, analytical, and communication abilities.

Career Development Events: Participate in networking sessions and career talks organized by LSE Careers, giving you the opportunity to connect with professionals and potential employers in the data science field.

Access to Advanced Research Facilities: Benefit from state-of-the-art computing resources and dedicated laboratories for data science research, supporting your academic progress and professional ambitions.

By blending these practical experiences with academic learning, the BSc Data Science program at LSE ensures that you’re not only prepared to tackle complex data challenges but also ready to make meaningful contributions in a rapidly changing field.

Progression & Future Opportunities

Career Opportunities for BSc Data Science Graduates at LSE

Graduates of the BSc Data Science program at the London School of Economics & Political Science (LSE) leave well-prepared to make an impact in data-driven industries. The program builds a strong foundation in data science, machine learning, statistics, and mathematics, with a special emphasis on applications in the social sciences. With this training, graduates can pursue a variety of exciting roles, including:

  • Data Scientist

  • Data Analyst

  • Quantitative Researcher

  • Machine Learning Engineer

University Support & Industry Connections

LSE provides extensive support to help students succeed and connect with employers:

  • LSE Careers Service: Offers personalized career advice, workshops, and networking opportunities to help students explore career paths and connect with potential employers.

  • Digital Skills Lab: Provides resources to develop essential digital and technical skills that are highly valued in today’s job market.

Employment Statistics & Salary Expectations

Graduates from LSE’s data science programs enjoy strong career prospects, with median starting salaries around £40,000, reflecting the high demand for skilled data professionals. Top sectors employing LSE graduates include financial and professional services, insurance, digital technology and data, as well as accounting and auditing.

University-Industry Partnerships

LSE fosters close connections with industry and research institutions to give students practical experience and exposure to cutting-edge data science:

  • Data Science Institute (DSI): Collaborates with institutions such as Imperial College London, supporting interdisciplinary research and giving students access to innovative applications of data science.

  • Turing University Network: LSE’s membership connects students to a broader network of data science research and innovation, enhancing learning and career opportunities.

Accreditation & Long-Term Value

The BSc Data Science program provides rigorous training that prepares students not only for immediate professional success but also for advanced academic study. Graduates benefit from LSE’s global reputation and extensive alumni network, which can be instrumental in advancing their careers.

Further Academic Progression

For those interested in continuing their studies, LSE offers a range of postgraduate programs to deepen expertise and explore specialized areas:

  • MSc Data Science: Advanced training in data science methods with a focus on statistical approaches.

  • MSc Applied Social Data Science: Designed for applying data science to social, economic, or political challenges.

  • MSc Media and Communications (Data and Society): Explores the role of data in modern society and communication.

  • MSc Operations Research and Analytics: Equips students to apply mathematical methods to real-world problems.

  • MSc Health Data Science: Focuses on analysing and evaluating health interventions, services, and policies.

  • MSc Geographic Data Science: Uses quantitative data to answer spatial and geographic social science questions.

  • MPA - Data Science for Public Policy: Offers an interdisciplinary approach to tackling public policy challenges using political science, economics, econometrics, and data science tools.

These postgraduate programs allow students to specialize, engage in interdisciplinary research, and advance further in both professional and academic careers.

Program Key Stats

£32,100
£ 29
Sept Intake : 14th Jan


9 %
No
Yes

Eligibility Criteria

A*AA
N/A
39
95

N/A
N/A
7.0
100

Additional Information & Requirements

Career Options

  • Data Scientist
  • Data Analyst
  • Business Analyst
  • Machine Learning Engineer
  • Artificial Intelligence Engineer
  • Data Engineer
  • Big Data Engineer
  • Statistician
  • Database Administrator
  • Quantitative Analyst
  • Risk Analyst
  • Financial Analyst
  • Operations Analyst
  • Research Scientist
  • Business Intelligence Developer
  • Data Architect
  • Cloud Data Engineer
  • Marketing Analyst
  • Healthcare Data Analyst
  • Social Media Analyst
  • Cybersecurity Analyst
  • Fraud Analyst
  • Product Analyst
  • Supply Chain Analyst
  •  

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