City of London, London, United Kingdom Hybrid / WFH Options
Intellect Group
recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Method Resourcing
learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Harnham - Data & Analytics Recruitment
lending strategy (SME or consumer lending preferred). Strong quantitative background (degree in Maths, Engineering, Physics, or similar). Experience building and maintaining predictive credit models. Fluency in Python (Pandas, NumPy, SciPy, Matplotlib) and SQL. Experience with advanced modelling techniques (e.g., Monte Carlo, Bayesian modelling) is a plus. Strong communicator. Commercial mindset and strong instincts around risk and return. Experience More ❯
data concepts effectively and confidently Build great relationships with Data Science, Technology, Finance, Collections, Ops and other stakeholders What you'll need Excellent SQL skills Python data science stack (pandas, NumPy, Jupyter notebooks, Plotly/matplotlib, etc) A drive to solve problems using data Experience in a management role What would be a bonus: Familiarity with Git Data visualization tool More ❯
and stakeholders. Familiarity with the Model Risk Management (MRM) lifecycle, including model documentation, testing, validation, and alignment with governance and compliance frameworks. Proficiency in Pythonand tools such as LangChain, Pandas, PyTorch/TensorFlow, and FastAPI. Strong understanding of prompt engineering, RAG pipelines, vector databases (e.g., FAISS, Chroma), and LLM evaluation strategies. Familiarity with software engineering best practices, including: REST API More ❯
tools (e.g.: Git, Docker, Kubernetes). Familiarity with AI platforms and frameworks such as LangChain, Llamaindex and, HugginFace. Expertise in data manipulation, data visualisation, and statistical modelling libraries (e.g.: pandas, NumPy, Matplotlib, scikit-learn). Skills in data visualisation tools (e.g.: Tableau, PowerBI). Excellent problem-solving and analytical skills. Skills & attributes Passion for leveraging data to drive social impact More ❯
strong foundation in statistics, probability, and machine learning fundamentals either through a STEM degree, formal training, or self-study. Fluency in Python and SQL, including experience with libraries like Pandas, Scikit-learn, or equivalent. Demonstrated ability to solve real-world problems pragmatically using data. Clear, structured communication especially the ability to explain complex topics simply. A growth mindset: curious, driven More ❯
in computer science , Mathematics, Statistics, Business Administration or related field Advanced knowledge of SQL (joins, aggregations, CTEs and window functions) Good knowledge of Python, including popular Data Science packages (pandas, matplotlib, seaborn, numpy , sklearn ) Familiarity with what is happening under the hood of popular Machine Learning algorithms Strong problem-solving skills and attention to detail Strong communication and collaboration skills More ❯
s or PhD degree in a quantitative field. Proven experience of large-scale data analysis and hypothesis testing. Strong proficiency in statistical analysis and predictive modeling. Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. Excellent problem-solving skills and attention to detail. Strong communication skills with the ability to present complex data More ❯
academic field Strong python programming skills as evidenced by earlier work in data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of More ❯
science and advanced analytics to generate business value and change, including optimisation of production processes Great knowledge of Python and in particular, the classic Python Data Science stack (NumPy, pandas, PyTorch, scikit-learn, etc) is required; Familiarity with PySpark is also desirable. A cloud platform experience (e.g Azure, AWS, GCP), we're using Azure in the team. Good SQL understanding More ❯
science and advanced analytics to generate business value and change, including optimisation of production processes Great knowledge of Python and in particular, the classic Python Data Science stack (NumPy, pandas, PyTorch, scikit-learn, etc) is required; Familiarity with PySpark is also desirable. A cloud platform experience (e.g Azure, AWS, GCP), we're using Azure in the team. Good SQL understanding More ❯
science and advanced analytics to generate business value and change, including optimisation of production processes Great knowledge of Python and in particular, the classic Python Data Science stack (NumPy, pandas, PyTorch, scikit-learn, etc) is required; Familiarity with PySpark is also desirable. A cloud platform experience (e.g Azure, AWS, GCP), were using Azure in the team. Good SQL understanding in More ❯
in data analytics including statistics, data visualization, and working with large data sets Basic understanding of TCP and UDP network protocols Extensive experience with Python and relevant data libraries (Pandas, Numpy/Scipy) Some familiarity with the details of modern computer systems and networks Experience with real time exchange market data and order entry a plus Profile You possess a More ❯
a similar role. Strong programming skills and a good understanding of software engineering principles and clean code practices. Expert-level knowledge of Python for machine learning and data manipulation (pandas, NumPy). Advanced experience with SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn More ❯
science and advanced analytics to generate business value and change, including optimisation of production processes Great knowledge of Python and in particular, the classic Python Data Science stack (NumPy, pandas, PyTorch, scikit-learn, etc) is required; Familiarity with PySpark is also desirable. A cloud platform experience (e.g Azure, AWS, GCP), were using Azure in the team. Good SQL understanding in More ❯
data science roles Creative problem-solving and solution scoping Strong grasp of mathematical, statistical concepts, and machine learning algorithms Proficiency in Python and data science libraries for example NumPy, Pandas, Scikit-learn, Keras SQL proficiency Experience with cloud environments for example Google Cloud Platform Version control management Ability to work efficiently without compromising quality Effective communication and data storytelling skills More ❯
a similar role. Strong programming skills and a good understanding of software engineering principles and clean code practices. Expert-level knowledge of Python for machine learning and data manipulation (pandas, NumPy). Advanced experience with SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn More ❯
south west london, south east england, united kingdom
Mars
science and advanced analytics to generate business value and change, including optimisation of production processes Great knowledge of Python and in particular, the classic Python Data Science stack (NumPy, pandas, PyTorch, scikit-learn, etc) is required; Familiarity with PySpark is also desirable. A cloud platform experience (e.g Azure, AWS, GCP), were using Azure in the team. Good SQL understanding in More ❯
coursework, internships, or self-initiated projects You've got practical Python skills - maybe from significant coursework, personal projects, or internships - and you're comfortable exploring data using libraries like pandas or numpy You've had hands-on experience with structured or semi-structured data, including tasks like designing schemas, cleaning messy datasets, or validating results - perhaps through coursework, Kaggle competitions More ❯
Experience delivering data science or data engineering solutions into production. You're comfortable writing production-grade code, not just notebooks. Strong Python and SQL skills, including the basic libraries (Pandas, Numpy, ScikitLearn). You value writing clean, maintainable, and tested code. Proven ability to design, build, and maintain data pipelines and tools from scratch that are reliable, maintainable, and scalable. More ❯
cases like Retrieval-Augmented Generation (RAG) and natural language analytics. What we are looking for in our candidate Essential Proficiency in Python and SQL, with experience in frameworks like Pandas, PySpark, and NumPy for large-scale data processing. Expertise in debugging and optimising distributed systems with a focus on scalability and reliability. Proven ability to design and implement scalable, fault More ❯
and technical teams Direct experience working with social and digital platforms such as Meta, Amazon, Google to onboard datasets an advantage Proficiency working with data in SQL and Python (Pandas, NumPy preferred) Knowledge of statistical testing methodologies Experience with BI tools (Tableau, PowerBI preferred) Experience with cloud computing services & solutions (AWS, Azure, GCP, Amazon Marketing Cloud, Snowflake) Experience working with More ❯
record of leading high-performing teams. Proven ability to build predictive models and extract insights from large, complex datasets. Advanced proficiency in Python and SQL, including libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn. Skilled in developing and deploying credit risk models, including scorecard thresholds, limit optimisation, and loss reduction. Experience with Monte Carlo simulations or Bayesian modelling (e.g. More ❯
