1 to 25 of 261 Pandas Jobs in London

MLflow, Kubeflow, Vertex AI, or similar technologies. Knowledge of workflow orchestration platforms such as Apache Airflow. Experience with data processing technologies such as Pandas, Apache Beam, Spark, or similar frameworks. Strong SQL skills and experience with analytical databases such as BigQuery, PostgreSQL, or ClickHouse. Familiarity with observability and monitoring tools ...

systems Familiarity with distributed computing frameworks such as Spark and Dask, cloud platforms such as AWS, Azure, and GCP, and analytics libraries such as pandas, numpy, and matplotlib Exposure to DevOps, DataOps, and MLOps concepts and best practices Experience with Python, PySpark, SQL, Airflow, Databricks, Kedro, Dask/RAPIDS, Docker ...

their potential impact on products. Key Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure ...

their potential impact on products. Key Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure ...

world problems. Experience of coaching junior data scientists/analysts. Experience in reviewing code and documentation to a high standard. Experience in using Python (pandas, numpy, scikit-learn). End-to-end experience of managing multiple data science and analytics projects in different industries and with different types of data ...

principles. Experience with cloud platforms (AWS, Google Cloud, Azure) and containerization technologies (Docker, Kubernetes). Familiarity with databases (SQL, NoSQL) and data processing tools (Pandas, NumPy). Soft Skills Excellent problem-solving skills. Strong communication abilities. Capability to work collaboratively in a team environment. Preferred Skills Experience with natural language ...

skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines ...

influence stakeholders as well as present complex findings clearly to both technical and non-technical audiencesStrong coding skills in Python (e.g. OOP, PySpark, Pandas, NumPy, etc) and experience with SQLStrong statistical & analytical skills (e.g. sampling methods), attention to detail, and a proactive empirical mindsetFamiliarity with data modelling & modern data tech ...

integer programming, heuristics) Fluent in Python (required) and other programming languages (preferred) with strong skills in applying DS, ML, and OR packages (scikit‐learn, pandas, numpy, gurobi, etc.) to solve real‐life problems and visualise the outcomes (e.g., seaborn) Proficient in working with cloud platforms (AWS preferred), code versioning ...

Proven ability to translate business problems into measurable analytical outcomes. Experience taking models from development into production environments. Python and associated data science ecosystem (Pandas, NumPy, Scikit‐learn). Machine learning techniques including classification, regression, clustering and anomaly detection. Experience with Generative AI, LLMs, RAG architectures or agent‐based ...

Linux environment Nice to have: Advanced data engineering experience in Python, e.g. with libraries like Dagster, Prefect etc Experience optimising dataframe code, e.g. in Pandas or ideally Polars Experience of machine learning techniques and related libraries and frameworks e.g. scikit-learn, Pytorch, Tensorflow etc Experience deploying and serving ML models ...

Excellent communication skills with the ability to communicate concepts clearly and precisely Experience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) databases; and iii) cloud platform services (AWS, GCP, Azure) NICE TO HAVES Experience as a Data Architect or Senior Manager Proven track record ...

analytical outcomes. Desirable Well developed experience in a Lloyd’s syndicate, managing agent, London Market broker or specialty (re)insurer. Python for data analysis (pandas/notebooks) and an appreciation of wider data science techniques, enough to collaborate credibly with Data Scientists and Actuarial. Hands‐on experience applying AI/ ...

ability to translate business problems into measurable analytical outcomes. Experience taking models from development into production environments. Technical SkillsPython and associated data science ecosystem (Pandas, NumPy, Scikit-learn).Machine learning techniques including classification, regression, clustering and anomaly detection. Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions. ...

from concept through to production. Strong technical knowledge, including proficiency in Python and experience with core data science and ML libraries (e.g., scikit-learn, pandas, PyTorch or TensorFlow). Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing. Familiarity with Generative ...

concept through to production. Strong technical knowledge, including expert-level Python proficiency and experience with core data science and ML libraries (e.g., scikit-learn, pandas, PyTorch or TensorFlow).Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing. Familiarity with Generative AI concepts ...

skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines ...

version control. Good understanding of algorithms, data structures, and software design principles. Familiarity with data manipulation and analysis tools such as Pandas, NumPy, and SQL. Experience with, or a strong willingness to develop skills in, the Power Platform, including Power Apps, Power Automate, Power Pages and Dataverse. Basic understanding ...

processing methods (streaming vs batch)Familiarity with commonly used data platforms (Databricks, Snowflake, BigQuery, PSQL, etc.), cloud platforms (AWS, Azure, GCP) and engineering tools (Pandas, Spark, dbt, LangChain, etc.)Exposure to modern software development practices, including version control (Git) and foundational concepts in DevOps and MLOps/LLMOps ...

scalable SaaS platform. Any other ad hoc duties that may be required from time to time Technical Requirements: Proven experience with Python, especially Pandas and NumPy Mastery of SQL and PostgreSQL: schema design, complex queries, indexing and performance optimisation, beyond basic querying Experience with pipeline orchestration and scheduling Proven ability ...

strong foundation in system design, data storage, and reliability with commonly used data platforms (Databricks, Snowflake, BigQuery, PSQL, etc.) and data engineering tools (e.g., Pandas, Spark, dbt, etc.). Hands-on experience with MLOps/LLMOps principles, including CI/CD for data workflows, automated agent evaluation (LangSmith, Opik, Langfuse ...

including Power Pivot, Power Query, DAX, data models and complex financial modelling. Working knowledge of Python for data manipulation and automation, for example using pandas and scripting against vendor APIs. Experience building or maintaining ETL and data pipelines and working with structured data at scale. Understanding of IT infrastructure ...

data quality testing IaC/Terraform - awareness or practical experience SC Clearance - active clearance required to start Desirable : Docker Airflow/AWS Glue Pandas Data Lakes/Data Warehouses Public sector or consultancy experience Agile delivery experience Experience working alongside data science/ML teams To be Considered: Please apply ...

technologies and identify opportunities to improve business efficiency through intelligent automation. Skills & Experience Strong Python programming skills with experience using libraries such as Pandas, NumPy, Scikit-learn, XGBoost or LightGBM, and Plotly, Rust, Typescript, Python or Matplotlib. Experience developing machine learning models for prediction, optimisation or classification. Strong SQL skills ...

development. Hands-on experience with SQL for data processing and analytics. Strong programming skills in Python , with experience using data science libraries such as Pandas, Numpy, Scikit-learn, and Keras/PyTorch . Experience with Databricks and Spark for data manipulation and querying. Prior experience in the retail industry, with ...