51 to 75 of 153 Pandas Jobs in London

scalable workflows. Help grow and shape the data science team and its role within the wider business. What We’re Looking For Strong technical foundation with proficiency in Python (Pandas, NumPy, Scikit-learn), SQL, and cloud platforms (GCP or AWS). Experience with modern data warehouses (BigQuery, Snowflake, Redshift). Proven experience in deploying machine learning models or optimisation algorithms More ❯

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 ❯

insights into actionable strategies. Your Skills & Experience We’re looking for a Data Scientist with: Strong experience in predictive modeling, customer analytics, or marketing data science. Proficiency in Python (Pandas, NumPy, Sci-Kit Learn) or similar tools. A proven track record of delivering impactful, data-driven solutions. Strong communication skills and the ability to translate complex insights for non-technical More ❯

insights into actionable strategies. Your Skills & Experience We’re looking for a Data Scientist with: Strong experience in predictive modeling, customer analytics, or marketing data science. Proficiency in Python (Pandas, NumPy, Sci-Kit Learn) or similar tools. A proven track record of delivering impactful, data-driven solutions. Strong communication skills and the ability to translate complex insights for non-technical More ❯

experience in machine learning applications such as recommendations, segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science teams. Deep knowledge of media More ❯

experience in machine learning applications such as recommendations, segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science teams. Deep knowledge of media More ❯

Data Science, with a proven track record of delivering impactful projects. Strong statistical and machine learning expertise, with the ability to apply and evaluate various algorithms. Proficiency in Python (Pandas), SQL, and data analytics tools. Experience deploying and evaluating ML models in production environments. Ability to interpret complex datasets, drawing meaningful insights to drive business decisions. Strong communication skills, with More ❯

experience in a data science or analytics role, preferably within the AI/ML industry. Expert-level proficiency in Python and extensive experience with data science libraries such as Pandas, NumPy, and Scikit-learn. Deep hands-on experience with deep learning frameworks, particularly PyTorch . Proven experience with statistical analysis , hypothesis testing, and data visualization techniques. Familiarity with computer vision More ❯

methodologies for analyzing and interpreting large datasets. Ability to apply statistical techniques 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 More ❯

graduated with a Computer Science/ML/AI related degree and Masters or a PhD. We prefer candidates with the following skills & knowledge: Coding in Python, including numpy, pandas, and object oriented programming Version control such as git Familiarity with machine learning concepts What do you get for all your hard work? A competitive compensation package (base + equity 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 ❯

A solid foundation in statistics, probability, and machine learning fundamentals—through a STEM degree, formal training, or self-study. Proficiency in Python and SQL, including experience with libraries like Pandas, Scikit-learn, or equivalents. Proven ability to solve real-world problems pragmatically using data. Clear, structured communication skills, especially in explaining complex topics simply. A growth mindset: curious, driven, humble More ❯

quantitative discipline Understanding of NLP algorithms and techniquesand/or experience with Large Language Models (fine tuning, RAG, agents) Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.) Have experience productionising machine learning models Are an expert in one of predictive modeling, classification, regression, optimisation or recommendation systems Have experience with Spark Have knowledge … information systems (GIS) Experience with cloud infrastructure Experience with graph technology and/or algorithms Our technology stack Python and associated ML/DS libraries (Scikit-learn, Numpy, LightlGBM, Pandas, LangChain/LangGraph, TensorFlow, etc...) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc. MLOps: Terraform, Docker, Airflow, MLFlow More information: Enjoy fantastic perks like private healthcare & dental insurance, a generous More ❯

skilled in one of reinforcement learning, predictive modelling (classification and regression) and have a solid understanding of recommendation systems Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.) Have experience with Spark Have experience in productionising machine learning modelsand/or real-time systems Have knowledge of DevOps technologies such as Docker and Terraform … experience with NLP, designing, fine-tunning and developing GenAI models and building agent AI systems Our technology stack Python and associated ML/DS libraries (Scikit-learn, Numpy, LightlGBM, Pandas, TensorFlow, etc...) PySpark AWS cloud infrastructure: EMR, ECS, S3, Athena, etc. MLOps: Terraform, Docker, Airflow, MLFlow, Jenkins On call statement: Please be aware that our Machine Learning Engineers are required 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 ❯

graduated with a Computer Science/ML/AI related degree and Masters or a PhD. We Prefer Candidates With The Following Skills & Knowledge Coding in Python, including numpy, pandas, and object oriented programming Version control such as git Familiarity with machine learning concepts What do you get for all your hard work? A competitive compensation package (base + equity More ❯

Machine Learning Engineer - SaaS - London (Tech stack: Machine Learning Engineer, Python, TensorFlow, PyTorch, scikit-learn, Keras, Natural Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, ONNX (Open Neural Network Exchange) We have several exciting … full training will be provided to fill any gaps in your skill set): Machine Learning Engineer, Python, TensorFlow, PyTorch, scikit-learn, Keras, Natural Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, ONNX (Open Neural More ❯

etc.) Experience with molecular property prediction and multi-objective optimization using machine learning and/or deep learning methods Experienced with common python toolkits for scientific computing (e.g., numpy, pandas, scipy), machine learning (e.g., scikit-learn, pytorch), and cheminformatics/bioinformatics (e.g., rdkit, openeye, biotite, biopython) Familiarity running simulations and training models on high-performance computing (GPU) environments for corporate More ❯

pySpark and SQL for data mining; additional experience and knowledge of Big Data tools preferred. Excellent 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 More ❯

pySpark and SQL for data mining; additional experience and knowledge of Big Data tools preferred. Excellent 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 More ❯

dbt, Airflow) Experience with loyalty-programme analytics or CRM platforms Knowledge of machine-learning frameworks (scikit-learn, TensorFlow) for customer scoring Technical Toolbox Data & modeling: SQL, Python/R, pandas, scikit-learn Dashboarding: Tableau or Power BI ETL & warehousing: dbt, Airflow, Snowflake/Redshift/BigQuery Experimentation: A/B testing platforms (Optimizely, VWO) Desired Skills and Experience 8+ years More ❯

and reporting workflows Present clear, actionable pricing insights to commercial and executive stakeholders Must-Haves Master's in Statistics, Econometrics, Data Science or related quantitative field Expert in Python (pandas, scikit-learn) and advanced SQL for large-scale data manipulation Proven track record running A/B tests or causal analyses on pricing levers Excellent communication-able to explain complex More ❯

analysis of microscopy images Hands-on experience integrating and analysing multi-modal biological data, such as transcriptomics, proteomics, or single-cell data. Proficiency in Python, including libraries such as Pandas, NumPy, scikit-learn Experience analysing deep learning model outputs, especially from vision models and working with biological image embeddings. Ability to evaluate model performance, interpret model outputs, and connect them More ❯

analysis of microscopy images Hands-on experience integrating and analysing multi-modal biological data, such as transcriptomics, proteomics, or single-cell data. Proficiency in Python, including libraries such as Pandas, NumPy, scikit-learn Experience analysing deep learning model outputs, especially from vision models and working with biological image embeddings. Ability to evaluate model performance, interpret model outputs, and connect them 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 ❯