101 to 125 of 141 Pandas Jobs in London

and data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or More ❯

and T&L domain experts Required Skills/Experience The ideal candidate will have the following: Be an expert Python programmer proficient in frameworks/libraries such as: Numpy, Pandas, Scikit-Learn, Langchain, Llamaindex, Azure AI Foundry amongst others. Must have Azure and be an expert with R&D on generative AI techniques Practical experience with GenAI techniques such as More ❯

and data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or More ❯

and data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or More ❯

and data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or More ❯

Data Scientist, your background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g. More ❯

model performance. What We're Looking For A Bachelor's degree in Computer Science, Mathematics, Electrical Engineering, or a related field. Strong experience with Python and data science libraries (Pandas, Scikit-learn, etc.). Solid understanding of machine learning concepts and algorithms . Interest in working with real-world industrial or sensor data . Exposure to Apache Airflow and/ More ❯

industry experience, or an MS with significant industry or research experience in the field • Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals • Experience with big data and scalable model More ❯

large data volumes with modern data processing tools (e.g., Hadoop/Spark/SQL). Experience with or ability to learn open-source software including machine learning packages (e.g., Pandas, scikit-learn) and data visualization technologies. Experience in the retail sector would be an added advantage. What you can expect from us We'll defy expectations with a comprehensive rewards More ❯

team-wide best practices for data access, documentation, and reproducibility. Desired Skills/Experience 4+ years of experience in data analytics or data engineering. High proficiency in Python (e.g., pandas, NumPy, matplotlib/seaborn) and SQL essential. Hands-on experience with BI tools (ideally Power BI) advantageous Familiarity with cloud-based data platforms (ideally Azure) advantageous. Strong problem-solving skills More ❯

team-wide best practices for data access, documentation, and reproducibility. Desired Skills/Experience 4+ years of experience in data analytics or data engineering. High proficiency in Python (e.g., pandas, NumPy, matplotlib/seaborn) and SQL essential. Hands-on experience with BI tools (ideally Power BI) advantageous Familiarity with cloud-based data platforms (ideally Azure) advantageous. Strong problem-solving skills More ❯

and model evaluation Experience in SQL and Python for advance analytics and modelling (experience with Snowflake, R, GitHub, and Jira is a plus) Experience using Python libraries such as pandas, scikit-learn, and statsmodels (or R equivalent) Experience using BI tools like Power BI or Tableau to communicate insights Experience mentoring or upskilling colleagues in analytics tools (such as SQL More ❯

and model evaluation Experience in SQL and Python for advance analytics and modelling (experience with Snowflake, R, GitHub, and Jira is a plus) Experience using Python libraries such as pandas, scikit-learn, and statsmodels (or R equivalent) Experience using BI tools like Power BI or Tableau to communicate insights Experience mentoring or upskilling colleagues in analytics tools (such as SQL More ❯

and have in-depth knowledge of how they work Python: You have built and deployed production-grade Python applications and you are familiar with data science libraries such as pandas and scikit-learn Tooling & Environment : DevOps: You have experience working with DevOps tooling, such as gitops, Kubernetes, CI/CD tools (we use buildkite) and Docker Cloud: You have worked More ❯

. Utilise SQL for data extraction, transformation, and analysis. Skills & Experience Proven experience working as a Pricing Analyst. Strong proficiency in SQL and Python (including data libraries such as pandas, NumPy, scikit-learn, etc.) Skilled in Power BI or equivalent visualisation platforms. Background in retail, ticketing, or loyalty environments preferred. Experience in clustering, segmentation, and data modelling. Location: Shepherds Bush More ❯

innovative language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and More ❯

innovative language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and More ❯

innovative language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and More ❯

AI Services). Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and DL models using More ❯

innovative language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and More ❯

innovative language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and More ❯

AI Services). Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and DL models using More ❯

efficiency and reliability Collaborate closely with traders, quants, and developers to design new tools and refine existing systems Required Skills & Experience Strong Python programming skills, including data analysis with Pandas Advanced SQL proficiency (PostgreSQL or equivalent) managing large-scale datasets Solid understanding of market data sources (Bloomberg, Refinitiv/Reuters, etc.) Experience with Linux system administration in a low-latency More ❯

efficiency and reliability Collaborate closely with traders, quants, and developers to design new tools and refine existing systems Required Skills & Experience Strong Python programming skills, including data analysis with Pandas Advanced SQL proficiency (PostgreSQL or equivalent) managing large-scale datasets Solid understanding of market data sources (Bloomberg, Refinitiv/Reuters, etc.) Experience with Linux system administration in a low-latency More ❯

efficiency and reliability Collaborate closely with traders, quants, and developers to design new tools and refine existing systems Required Skills & Experience Strong Python programming skills, including data analysis with Pandas Advanced SQL proficiency (PostgreSQL or equivalent) managing large-scale datasets Solid understanding of market data sources (Bloomberg, Refinitiv/Reuters, etc.) Experience with Linux system administration in a low-latency More ❯