frameworks (TensorFlow, PyTorch, scikit-learn) - Skilled in handling large datasets, data wrangling, and statistical modelling - Comfortable working independently on end-to-end ML pipelines - Experienced in visualisation tools (e.g. Matplotlib, Seaborn, Tableau) Desirable: - Exposure to cloud platforms (AWS, GCP, Azure) and big data tools (Hadoop, Spark) - MSc/PhD in Computer Science, AI, Data Science, or related field More ❯
to validate models and algorithms. Data Manipulation & Analysis: Proficient in data manipulation and analysis using tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau to communicate insights effectively. Our offer: Cash: Depends on experience Equity: Generous equity package, on a standard vesting schedule Impact & Exposure: Work at the leading edge of More ❯
Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualisation and API libraries (matplotlib, plotly, streamlit, Flask, etc). Understanding of Gen AI models, Vector databases, Agents, and follow the market trends. Its desirable to have a hands-on experience on these. Substantial experience More ❯
Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualisation and API libraries (matplotlib, plotly, streamlit, Flask, etc). Understanding of Gen AI models, Vector databases, Agents, and follow the market trends. Its desirable to have a hands-on experience on these. Substantial experience More ❯
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 Ability More ❯
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 for solving complex More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Intellect Group
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 for solving complex More ❯
learn, XGBoost, LightGBM, StatsModels PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working with cloud More ❯
business problems Proven experience in translating technical methods to non-technical stakeholders Strong programming experience in python (R, Python, C++ optional) and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain) Experience with version control (GitHub) ML experience with causality, Bayesian statistics & optimization, survival analysis, design of experiments, longitudinal analysis, surrogate More ❯
data catalogs, metadata management, vector databases, relational/object databases. Experience with Kubernetes. Understanding of computational geometry (meshes, boundary representations). Ability to analyze data using tools like Pandas, Matplotlib, Seaborn, Plotly, R. Familiarity with Autodesk or similar CAD/CAE/CAM products. Knowledge of data lake architectures, data provenance, and lineage. Understanding of computational geometry and industry-specific More ❯
learning algorithms, particularly tree-based models, and their application to structured data Familiarity with SQL and experience working with relational databases. Python/R programming experience (pandas, scikit-learn, matplotlib, etc) Excellent problem-solving skills and the ability to work in a fast-paced environment. Strong communication skills to effectively collaborate with team members and present findings to stakeholders. A More ❯
learning algorithms, particularly tree-based models, and their application to structured data Familiarity with SQL and experience working with relational databases. Python/R programming experience (pandas, scikit-learn, matplotlib, etc) Excellent problem-solving skills and the ability to work in a fast-paced environment. Strong communication skills to effectively collaborate with team members and present findings to stakeholders. A More ❯
learning algorithms, particularly tree-based models, and their application to structured data. Familiarity with SQL and experience working with relational databases. Python/R programming experience (pandas, scikit-learn, matplotlib, etc) Excellent problem-solving skills and the ability to work in a fast-paced environment. Strong communication skills to effectively collaborate with team members and present findings to stakeholders. A More ❯
year. They code in Python, and React on the Frontend. Tech & Data Science stack: Kubernetes & Docker on Google Cloud Python 3: Pandas, RabbitMQ, Celery, Flask, SciPy, NumPy, Dash, Plotly, Matplotlib Javascript, React, Redux PostgreSQL, Redis Prometheus, Alert Manager, DataDog If you joined the company in a Data Science role you would be working on sophisticated pricing algorithms which would enable More ❯
West London, London, England, United Kingdom Hybrid / WFH Options
Bond Williams
findings in a clear, concise manner. Collaborate with the data engineering team to maintain good data hygiene and integration. Essential Requirements Proficiency in Python for data analysis (pandas, NumPy, matplotlib/seaborn). Solid foundation in statistics: distributions, hypothesis testing, confidence intervals, regression. Experience working with structured datasets Ability to produce clear, well-commented code and visual outputs (e.g. plots More ❯
skills regarding data analysis, statistics, and programming. Strong working knowledge of, Python, Hadoop, SQL, and/or R. Working knowledge of Python data tools (e.g. Jupyter, Pandas, Scikit-Learn, Matplotlib). Ability to talk the language of statistics, finance, and economics a plus. Profound knowledge of the English language. In a changing world, diversity and inclusion are core values for More ❯
other stakeholders. What you'll need Excellent SQL skills. A drive to solve problems using data. Proficiency with the Python data science stack (pandas, NumPy, Jupyter notebooks, Plotly/matplotlib, etc.). Bonus skills include: Familiarity with Git. Experience with data visualization tools (Tableau, Looker, PowerBI, or equivalent). Knowledge of DBT. 2-5 years of experience in consumer credit More ❯
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 (Tableau, Looker, PowerBI or equivalent) DBT More ❯
driven analysis and guide this work through others. Experienced in using Python and SQL to query and analyse large datasets, with expertise in libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn for data manipulation, statistical analysis, and visualisation. Familiarity with Monte Carlo simulations in Python and/or PyMC3 for Bayesian modelling is a plus. Familiarity with statistical confidence More ❯
e.g. NLP, Transfer Learning etc) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc) Solid knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib, etc) Understanding of model evaluation, data pre-processing techniques, such as standardisation, normalisation, and handling missing data Solid understanding of summary, robust, and nonparametric statistics; hypothesis testing, probability distributions, sampling More ❯
e.g., NLP, Transfer Learning, etc.), and modern Deep Learning algorithms (e.g., BERT, LSTM, etc.) Solid knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib, etc.) Understanding of model evaluation, data pre-processing techniques, such as standardisation, normalisation, and handling missing data Solid understanding of summary, robust, and nonparametric statistics; hypothesis testing; probability distributions; sampling More ❯
ML algorithms (e.g., Logistic Regression, Random Forest, XGBoost), research areas (e.g., NLP, Transfer Learning), and Deep Learning (e.g., BERT, LSTM) Proficiency in SQL and Python (Jupyter, Pandas, Scikit-learn, Matplotlib) Knowledge of model evaluation, data preprocessing techniques, and statistical methods Core Values Customer Focus: Use data to improve customer experience Humanity: Act with respect and integrity Curiosity: Build and share More ❯
London, England, United Kingdom Hybrid / WFH Options
Harnham
both technical teams and business users. A self-starter who is proactive, detail-oriented, and committed to delivering value. 🌟 Nice to Have: Some experience in Python (e.g., pandas, seaborn, matplotlib). Familiarity with cloud platforms (AWS, Azure). Previous exposure to transport/rail industry data or commercial systems. If you are interested in this role, please apply. To follow More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Harnham - Data & Analytics Recruitment
both technical teams and business users. A self-starter who is proactive, detail-oriented, and committed to delivering value. Nice to Have: Some experience in Python (e.g., pandas, seaborn, matplotlib). Familiarity with cloud platforms (AWS, Azure). Previous exposure to transport/rail industry data or commercial systems. If you are interested in this role, please apply. To follow More ❯
