82 Data Science jobs in Cambridge

Our client is offering an exceptional opportunity for talented and ambitious individuals to join their team as an Advanced Apprentice in Data Science, based in the vibrant academic hub of Cambridge, Cambridgeshire, UK . This apprenticeship is designed for motivated individuals who have recently completed their A-levels or equivalent qualifications and are eager to launch a career in the rapidly evolving field of data science. You will gain hands-on experience working with real-world data, develop advanced analytical skills, and learn to apply statistical and machine learning techniques to solve complex business problems. The apprenticeship combines practical, on-the-job training with structured learning, leading to a recognised qualification. Responsibilities include data collection, cleaning, and preprocessing; assisting in the development and implementation of predictive models; creating visualizations and reports to communicate insights; and collaborating with experienced data scientists and analysts. This role embraces a hybrid working model, providing valuable office experience alongside the flexibility of remote work. You will have the chance to work on diverse projects across various industries, contributing to data-driven decision-making. We are seeking individuals with a strong aptitude for numbers, a curious mind, and a passion for learning. A good understanding of mathematics and statistics is essential. Previous exposure to programming languages like Python or R, while not essential, would be advantageous. This apprenticeship is an ideal stepping stone for a successful career in data science, offering comprehensive training, mentorship, and clear progression pathways. If you are looking to kick-start your career with a leading organisation and gain invaluable skills in a high-demand field, this is the perfect opportunity. Join a team that values innovation, collaboration, and continuous learning in the heart of scientific advancement.
Requirements:

• Recently completed A-levels (or equivalent) with strong grades in Maths or a science subject.
• A keen interest in data, analytics, and technology.
• Strong problem-solving abilities and attention to detail.
• Excellent communication and teamwork skills.
• Eagerness to learn and adapt to new technologies and methodologies.
• Willingness to undertake a structured apprenticeship program.
• Basic understanding of programming concepts is a plus.
• Must be eligible to work in the UK and meet apprenticeship funding criteria.

Our client is excited to offer a highly sought-after Graduate Programme in Data Science, based at their cutting-edge facility in **Cambridge, Cambridgeshire**. This programme is designed for ambitious and intellectually curious recent graduates who are passionate about leveraging data to solve complex problems and drive innovation. Over the course of this intensive programme, you will gain hands-on experience with real-world data sets, working alongside experienced data scientists and researchers. You will be exposed to a wide range of techniques and tools, including machine learning, statistical modeling, data visualisation, and big data technologies. The programme provides a structured learning path, combining theoretical knowledge with practical application. Key learning areas will include data preprocessing, feature engineering, model development, evaluation, and deployment. You will have the opportunity to contribute to impactful projects across various business domains, developing your analytical and problem-solving skills. The role requires a strong foundation in mathematics, statistics, and programming (Python, R). Familiarity with SQL and database concepts is also beneficial. We are looking for individuals who are eager to learn, possess strong critical thinking abilities, and have excellent communication skills to articulate their findings. The programme encourages collaboration and teamwork, providing a supportive environment for professional growth. This is an exceptional opportunity to kick-start your career in data science within a leading organisation, renowned for its commitment to research and development. The programme offers mentorship, networking opportunities, and a clear pathway towards a full-time role upon successful completion. Successful candidates will be instrumental in helping our client make data-driven decisions and unlock new opportunities. The role demands intellectual curiosity and a proactive approach to learning and development.
Responsibilities:

• Assist in the collection, cleaning, and transformation of large datasets.
• Support the development and implementation of statistical models and machine learning algorithms.
• Conduct exploratory data analysis and create visualisations to uncover insights.
• Contribute to the evaluation and validation of predictive models.
• Work with senior data scientists on ongoing research and development projects.
• Document methodologies, findings, and code.
• Collaborate with cross-functional teams to understand data needs and deliver solutions.
• Participate in training sessions and workshops to enhance technical skills.
• Assist in preparing reports and presentations of analytical results.
• Adhere to data privacy and security best practices.

Qualifications:

• A Bachelor's or Master's degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, Physics, or a related discipline.
• Strong understanding of statistical concepts and machine learning principles.
• Proficiency in programming languages like Python or R.
• Familiarity with SQL and database querying.
• Excellent analytical and problem-solving skills.
• Strong communication and interpersonal abilities.
• Eagerness to learn and adapt to new technologies.
• Ability to work effectively in a team environment.
• Previous internship or project experience in data analysis is a plus.

Our client is delighted to offer a prestigious Data Science Graduate Fellowship, a fully remote opportunity perfect for bright minds eager to launch their careers in **Cambridge, Cambridgeshire, UK**. This fellowship is designed for recent graduates or those nearing completion of their degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Economics). You will join a world-class team of data scientists and researchers, gaining hands-on experience in cutting-edge data analysis, machine learning, and predictive modeling. As a fellow, you will work on real-world projects, contributing to innovative solutions that drive business insights and product development. The role requires a strong foundation in statistical concepts, programming skills (preferably Python or R), and a passion for data. You will be responsible for data cleaning, feature engineering, model development, validation, and interpretation. Collaboration is key, and you will work closely with senior data scientists, mentors, and other stakeholders, using virtual collaboration tools to ensure seamless project execution. This is a remote-first role, demanding strong self-management, excellent communication, and a proactive attitude. We are looking for curious, analytical individuals with a drive to learn and make a tangible impact. The fellowship provides an unparalleled opportunity to develop your skills, build a professional network, and gain invaluable experience in a highly sought-after field, all from your chosen location within or around **Cambridge, Cambridgeshire, UK**. You will be exposed to a wide range of data science techniques and tools, receiving mentorship from leading experts in the field. The program is structured to foster professional growth and provide a clear pathway for future career development within data science. Successful fellows will demonstrate strong problem-solving capabilities, a meticulous approach to data handling, and the ability to articulate complex findings clearly. This fellowship is an ideal stepping stone for aspiring data scientists looking to gain practical experience and contribute to impactful projects in a flexible, remote setting.

Our client, a leading research institution in Cambridge, Cambridgeshire, UK , is looking for bright and ambitious Data Science Graduate Analysts to join their innovative team. This is an exceptional opportunity for recent graduates with a passion for data, analytics, and cutting-edge technology to kick-start their careers in a challenging and supportive environment. You will be involved in complex projects, gaining invaluable experience in data manipulation, statistical analysis, machine learning, and data visualization.

As a Data Science Graduate Analyst, your responsibilities will include:

• Assisting senior data scientists in collecting, cleaning, and pre-processing large datasets from various sources.
• Performing exploratory data analysis to identify trends, patterns, and insights.
• Contributing to the development and implementation of predictive models and machine learning algorithms.
• Visualizing data and presenting findings clearly and concisely to technical and non-technical stakeholders.
• Collaborating with cross-functional teams to understand data needs and deliver actionable recommendations.
• Participating in code reviews and contributing to the development of robust data pipelines.
• Staying up-to-date with the latest advancements in data science and artificial intelligence.
• Documenting methodologies, processes, and results thoroughly.
• Supporting the maintenance and improvement of existing analytical tools and platforms.
• Undertaking specific analytical tasks and projects as assigned by the management team.

To be considered for this role, you must have recently completed or be in the final stages of completing a degree in a quantitative field such as Computer Science, Statistics, Mathematics, Physics, or a related discipline. Strong programming skills in Python or R, along with experience in SQL, are essential. Familiarity with data visualization tools (e.g., Tableau, Power BI) and machine learning libraries (e.g., Scikit-learn, TensorFlow) is highly desirable. Excellent analytical thinking, problem-solving abilities, and a keen eye for detail are crucial. This role is based in Cambridge, Cambridgeshire, UK and offers a hybrid working model, allowing for a balance between in-office collaboration and remote flexibility.

Our client is a leading recruitment consultancy renowned for its expertise in placing top-tier technology talent. We are currently seeking a highly motivated and experienced Senior Technical Recruiter to join our fully remote team. Specializing in Artificial Intelligence and Data Science roles, you will be instrumental in identifying, engaging, and securing highly sought-after professionals for our diverse client base. This role offers the flexibility of remote work across the UK, allowing you to leverage your sourcing strategies and network from wherever you work best. You will build strong relationships with candidates and clients, manage the full recruitment lifecycle, and contribute to the growth of our specialized vertical.

Key Responsibilities:

• Manage the end-to-end recruitment process for AI and Data Science positions, from sourcing to offer negotiation.
• Develop and execute innovative sourcing strategies to identify passive and active candidates across various platforms (LinkedIn Recruiter, GitHub, Stack Overflow, niche job boards).
• Conduct in-depth candidate screenings and technical interviews to assess skills, experience, and cultural fit.
• Build and maintain a strong talent pipeline for critical AI and Data Science roles.
• Collaborate closely with hiring managers to understand their technical requirements and hiring needs.
• Provide expert market intelligence and insights on AI/Data Science talent trends.
• Negotiate competitive compensation packages and facilitate the offer process.
• Maintain accurate candidate records in our Applicant Tracking System (ATS).
• Contribute to business development efforts by identifying potential new clients and opportunities.
• Stay updated on the latest advancements and talent demands within the AI and Data Science fields.

Qualifications:

• Proven experience as a Technical Recruiter, with a strong focus on AI, Machine Learning, Data Science, or related fields.
• Demonstrated success in sourcing and hiring niche technical talent.
• Expertise in using various recruitment tools and platforms, including LinkedIn Recruiter, ATS, and Boolean search techniques.
• Excellent understanding of AI/ML concepts, programming languages (Python, R), and data science methodologies.
• Strong interviewing and assessment skills.
• Exceptional communication, interpersonal, and negotiation skills.
• Ability to work independently, manage multiple priorities, and thrive in a fast-paced, remote environment.
• Bachelor's degree in a relevant field or equivalent practical experience.

This fully remote opportunity, while based with a company often serving clients in the Cambridge, Cambridgeshire, UK area, provides the ultimate flexibility for talented recruiters to excel from any UK location.

At Microsoft Research AI for Science ( , we believe machine learning and artificial intelligence has the potential to transform scientific modelling and discovery crucial for solving the most pressing problems facing society including sustainable materials and discovery of new drugs.



We seek a highly motivated Senior RSDE to join our Biomolecular Emulator (BioEmu) team. The BioEmu project aims to model the dynamics and function of proteins - how they change shape, bind to each other, and bind small molecules. This approach will help us to understand biological function and dysfunction on a structural level and lead to more effective and targeted drug discovery. Our BioEmu-1 model was published in Science ( (see our blog post ( for links to our open-source software and other resources and this explainer video ( ).



**Responsibilities**


Data integration for structure & dynamics: Build ingestion/curation pipelines for structural/biophysical data (mmCIF/PDB, EM maps/particles, binding/biophysics, spectroscopy); implement map/volume preprocessing (e.g., resolution filtering, normalization) and alignment to model inputs/outputs.
Cryou2011EM expertise: Operationalize endu2011tou2011end flows from raw image stacks/particles to 3D maps and modelu2011ready tensors; interoperate with community formats (e.g., EMDB/EMPIAR, mmCIF) and link to sequences/annotations.
Signal & information content: Design dataset diagnostics (e.g., mutualu2011informationu2011like measures, effective sample size, SNR proxies) to quantify what data teach the model; build activeu2011learning loops that maximize learning per euro of data collection time.
Modelu2011aware data services: Implement scalable, versioned data services and feature stores that feed training/evaluation; design loaders/augmentations optimized for throughput and correctness (GPUu2011aware).
Trainingu2011atu2011scale engineering: Own distributed data pipelines and orchestration for large runs on Azure; profile and tune I/O, storage tiers, data locality, and caching; monitor cost, utilization, and failure modes.
Quality, governance, and reproducibility: Codify schemas/ontologies, metadata contracts, unit/integration tests, and lineage; automate validation and data drift detection; maintain documentation and examples.
Partner across disciplines: Work closely with ML researchers, structural biologists, and drug designers; translate experimental constraints into robust computational workflows; communicate clearly and proactively.



**Qualifications**



Required:


PhD or equivalent experience in Computer Science, Machine Learning, Applied Mathematics, Computational Biology, or related field.
Strong software engineering in Python (packaging, testing, CI), with systems thinking for datau2011intensive ML.
Deep learning experience (PyTorch/JAX/TensorFlow) and solid foundations in linear algebra, probability, and statistics.
Proven experience designing robust data pipelines for largeu2011scale ML (HPC or cloud).
Ability to reason about learning signal and to assess information content of realu2011world scientific datasets.
Excellent collaboration and communication in interdisciplinary teams.



Preferred:


Handsu2011on cryou2011EM experience (e.g., map reconstruction, refinement, or pipeline tooling).
CUDA or C++ for performanceu2011critical components; experience with mixed precision and memoryu2011efficient training.
Experience integrating experimental data into ML models (e.g., constraints/priors from cryou2011EM, binding assays, spectroscopy).
Familiarity with MD data, structure prediction systems, or protein design work-flows.
Experience with costu2011optimization for data collection and cloud utilization; clear track record of building reliable, maintainable research software at scale.
Experience with structural biology or molecular biology data/techniques (e.g., cryou2011EM, binding assays, spectroscopy, expression, sequencing)



#Research #AI for Science



Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations ( .

At Microsoft Research AI for Science ( , we believe machine learning and artificial intelligence has the potential to transform scientific modelling and discovery crucial for solving the most pressing problems facing society including sustainable materials and discovery of new drugs.



We seek a highly motivated Senior RSDE to join our Biomolecular Emulator (BioEmu) team. The BioEmu project aims to model the dynamics and function of proteins - how they change shape, bind to each other, and bind small molecules. This approach will help us to understand biological function and dysfunction on a structural level and lead to more effective and targeted drug discovery. Our BioEmu-1 model was published in Science ( (see our blog post ( for links to our open-source software and other resources and this explainer video ( ).



**Responsibilities**


Data integration for structure & dynamics: Build ingestion/curation pipelines for structural/biophysical data (mmCIF/PDB, EM maps/particles, binding/biophysics, spectroscopy); implement map/volume preprocessing (e.g., resolution filtering, normalization) and alignment to model inputs/outputs.
Cryou2011EM expertise: Operationalize endu2011tou2011end flows from raw image stacks/particles to 3D maps and modelu2011ready tensors; interoperate with community formats (e.g., EMDB/EMPIAR, mmCIF) and link to sequences/annotations.
Signal & information content: Design dataset diagnostics (e.g., mutualu2011informationu2011like measures, effective sample size, SNR proxies) to quantify what data teach the model; build activeu2011learning loops that maximize learning per euro of data collection time.
Modelu2011aware data services: Implement scalable, versioned data services and feature stores that feed training/evaluation; design loaders/augmentations optimized for throughput and correctness (GPUu2011aware).
Trainingu2011atu2011scale engineering: Own distributed data pipelines and orchestration for large runs on Azure; profile and tune I/O, storage tiers, data locality, and caching; monitor cost, utilization, and failure modes.
Quality, governance, and reproducibility: Codify schemas/ontologies, metadata contracts, unit/integration tests, and lineage; automate validation and data drift detection; maintain documentation and examples.
Partner across disciplines: Work closely with ML researchers, structural biologists, and drug designers; translate experimental constraints into robust computational workflows; communicate clearly and proactively.



**Qualifications**



Required:


PhD or equivalent experience in Computer Science, Machine Learning, Applied Mathematics, Computational Biology, or related field.
Strong software engineering in Python (packaging, testing, CI), with systems thinking for datau2011intensive ML.
Deep learning experience (PyTorch/JAX/TensorFlow) and solid foundations in linear algebra, probability, and statistics.
Proven experience designing robust data pipelines for largeu2011scale ML (HPC or cloud).
Ability to reason about learning signal and to assess information content of realu2011world scientific datasets.
Excellent collaboration and communication in interdisciplinary teams.



Preferred:


Handsu2011on cryou2011EM experience (e.g., map reconstruction, refinement, or pipeline tooling).
CUDA or C++ for performanceu2011critical components; experience with mixed precision and memoryu2011efficient training.
Experience integrating experimental data into ML models (e.g., constraints/priors from cryou2011EM, binding assays, spectroscopy).
Familiarity with MD data, structure prediction systems, or protein design work-flows.
Experience with costu2011optimization for data collection and cloud utilization; clear track record of building reliable, maintainable research software at scale.
Experience with structural biology or molecular biology data/techniques (e.g., cryou2011EM, binding assays, spectroscopy, expression, sequencing)



#Research #AI for Science



Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations ( .

At Microsoft Research AI for Science ( , we believe machine learning and artificial intelligence has the potential to transform scientific modelling and discovery crucial for solving the most pressing problems facing society including sustainable materials and discovery of new drugs.
We seek a highly motivated Senior RSDE to join our Biomolecular Emulator (BioEmu) team. The BioEmu project aims to model the dynamics and function of proteins - how they change shape, bind to each other, and bind small molecules. This approach will help us to understand biological function and dysfunction on a structural level and lead to more effective and targeted drug discovery. Our BioEmu-1 model was published in Science ( (see our blog post ( for links to our open-source software and other resources and this explainer video ( ).
**Responsibilities**
+ Data integration for structure & dynamics: Build ingestion/curation pipelines for structural/biophysical data (mmCIF/PDB, EM maps/particles, binding/biophysics, spectroscopy); implement map/volume preprocessing (e.g., resolution filtering, normalization) and alignment to model inputs/outputs.
+ Cryo‑EM expertise: Operationalize end‑to‑end flows from raw image stacks/particles to 3D maps and model‑ready tensors; interoperate with community formats (e.g., EMDB/EMPIAR, mmCIF) and link to sequences/annotations.
+ Signal & information content: Design dataset diagnostics (e.g., mutual‑information‑like measures, effective sample size, SNR proxies) to quantify what data teach the model; build active‑learning loops that maximize learning per euro of data collection time.
+ Model‑aware data services: Implement scalable, versioned data services and feature stores that feed training/evaluation; design loaders/augmentations optimized for throughput and correctness (GPU‑aware).
+ Training‑at‑scale engineering: Own distributed data pipelines and orchestration for large runs on Azure; profile and tune I/O, storage tiers, data locality, and caching; monitor cost, utilization, and failure modes.
+ Quality, governance, and reproducibility: Codify schemas/ontologies, metadata contracts, unit/integration tests, and lineage; automate validation and data drift detection; maintain documentation and examples.
+ Partner across disciplines: Work closely with ML researchers, structural biologists, and drug designers; translate experimental constraints into robust computational workflows; communicate clearly and proactively.
**Qualifications**
Required:
+ PhD or equivalent experience in Computer Science, Machine Learning, Applied Mathematics, Computational Biology, or related field.
+ Strong software engineering in Python (packaging, testing, CI), with systems thinking for data‑intensive ML.
+ Deep learning experience (PyTorch/JAX/TensorFlow) and solid foundations in linear algebra, probability, and statistics.
+ Proven experience designing robust data pipelines for large‑scale ML (HPC or cloud).
+ Ability to reason about learning signal and to assess information content of real‑world scientific datasets.
+ Excellent collaboration and communication in interdisciplinary teams.
Preferred:
+ Hands‑on cryo‑EM experience (e.g., map reconstruction, refinement, or pipeline tooling).
+ CUDA or C++ for performance‑critical components; experience with mixed precision and memory‑efficient training.
+ Experience integrating experimental data into ML models (e.g., constraints/priors from cryo‑EM, binding assays, spectroscopy).
+ Familiarity with MD data, structure prediction systems, or protein design work-flows.
+ Experience with cost‑optimization for data collection and cloud utilization; clear track record of building reliable, maintainable research software at scale.
+ Experience with structural biology or molecular biology data/techniques (e.g., cryo‑EM, binding assays, spectroscopy, expression, sequencing)
#Research #AI for Science
Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations ( .

Our client, a leading entity in resource exploration and geological analysis, is seeking a highly skilled Geologist with expertise in Remote Sensing and Data Analysis to join their globally distributed team. This is a fully remote position, offering the opportunity to work on diverse geological projects from anywhere. The role will involve the interpretation of satellite imagery, geophysical data, and other remote sensing products to identify and assess mineral and resource deposits. The ideal candidate will possess a strong foundation in geology, advanced analytical skills, and extensive experience with relevant software and technologies.

Responsibilities:

• Utilize remote sensing data (e.g., satellite imagery, LiDAR, SAR) to identify geological features, structures, and potential resource targets.
• Process, analyze, and interpret various types of geological and geophysical data, including seismic, magnetic, and gravity data.
• Develop and apply advanced data analysis techniques and algorithms for geological modeling and interpretation.
• Integrate diverse datasets to create comprehensive geological models and maps.
• Conduct literature reviews and historical data analysis to support exploration and resource assessment efforts.
• Prepare detailed technical reports, presentations, and geological maps for internal and external stakeholders.
• Collaborate virtually with geologists, geophysicists, data scientists, and other team members located worldwide.
• Contribute to the development and refinement of data processing workflows and analytical methodologies.
• Stay abreast of the latest advancements in remote sensing technologies, geological software, and data analysis techniques.
• Ensure data quality, integrity, and consistency throughout all analytical processes.
• Assist in the planning and execution of geological surveys and exploration programs.
• Provide geological expertise and insights to support decision-making in resource development projects.
• Maintain and manage geological databases and datasets.

Qualifications:

• Master's or Ph.D. in Geology, Geophysics, Remote Sensing, or a closely related field.
• Minimum of 5-7 years of professional experience in geological exploration, with a specific focus on remote sensing and data analysis.
• Proficiency in geological software (e.g., ArcGIS, QGIS, Leapfrog, Petrel) and remote sensing software (e.g., ERDAS Imagine, ENVI).
• Strong programming skills in languages such as Python, R, or MATLAB for data analysis and scripting.
• Experience with GIS and spatial analysis techniques.
• In-depth understanding of geological principles, mineral deposit types, and exploration methods.
• Familiarity with various remote sensing platforms and data acquisition methods.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong written and verbal communication skills, with the ability to clearly present complex technical information.
• Ability to work independently and manage multiple projects effectively in a remote setting.
• Experience with machine learning applications in geology is a significant advantage.
• Membership in professional geological societies is desirable.

This is a fantastic opportunity for a motivated geologist to contribute to impactful projects within a flexible, remote work environment.