1 to 25 of 45 Remote/Hybrid 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 ...

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 ...

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 ...

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 ...

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 ...

least 2 years’ experience working as a data engineer (ideally consulting/financial services) – salary and level will reflect experience. Proficiency in Python (pandas, numpy) Professional experience with Azure cloud services (AWS/GCP acceptable with deeper experience) Strong experience deploying clean, maintainable, production-level code. Basic understanding ...

delivering production-ready models that drive measurable business value. Technical Proficiency: Strong expertise in Python and SQL. Deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (such as PyTorch, XGBoost, or LightGBM). Engineering Rigor: Proven ability to build for production. Experience working ...

stress-testing, simulation analysis, rare event modeling, and stochastic modeling preferred but not required. Substantial experience with Python, R, and relevant libraries (e.g., numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot, etc.). Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g., SQL, Selenium ...

stress-testing, simulation analysis, rare event modeling, and stochastic modeling preferred but not required. Substantial experience with Python, R, and relevant libraries (e.g., numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot, etc.). Proven experience developing, refining, and monitoring NLP models. Familiarity with database management tools and techniques (e.g., SQL, Selenium ...

least one primary backend language: Java (Modern Java, Spring Boot, concurrency, low-latency tuning, GC optimization), OR Python (Modern Python, asynchronous programming, NumPy/Pandas, FastAPI), OR .NET/C# (Modern .NET Core, multi-threading, asynchronous I/O, memory profiling). Distributed Systems & Messaging: Strong experience with enterprise messaging ...

years of it, but you should be able to reason about a model rather than only consume one. Python — working exposure to data manipulation (pandas, PySpark or similar). You will use it here from early on, so some practical experience is needed even if it is not your strongest ...

Python for automation, parsing, rules engines, and data quality checks, ability to write maintainable code. Experience using Python packages for data wrangling (e.g. Pandas, Polars), modelling (e.g. scikit-learn) and visualization (e.g. matplotlib) Experience with modern data tooling (for example, Spark, Azure Data Factory) or ability to implement equivalents with ...

Python and SQL Strong foundation in mathematics and statistics Proficiency in Python, including relevant libraries for data analysis and machine learning (e.g. sklearn, Pandas, NumPy) Knowledge of data analysis techniques, such as statistical modelling and visualisation, to draw insight from data Familiarity with Git as part of the development process ...

need everything) Experience of working in an Agile delivery team Strong analytic skills related to working with unstructured datasets Python (PySpark, Pandas, PyArrow) Distributed data processing (Apache Spark) Data ETL (Apache Airflow, AWS Step Functions, Apache NiFi) Cloud services (AWS, Azure or GCP) Messaging/Streaming (Kafka, AWS SQS, Other ...

need everything) Experience of working in an Agile delivery team Strong analytic skills related to working with unstructured datasets Python (PySpark, Pandas, PyArrow) Distributed data processing (Apache Spark) Data ETL (Apache Airflow, AWS Step Functions, Apache NiFi) Cloud services (AWS, Azure or GCP) Messaging/Streaming (Kafka, AWS SQS, Other ...

need everything) Experience of working in an Agile delivery team Strong analytic skills related to working with unstructured datasets Python (PySpark, Pandas, PyArrow) Distributed data processing (Apache Spark) Data ETL (Apache Airflow, AWS Step Functions, Apache NiFi) Cloud services (AWS, Azure or GCP) Messaging/Streaming (Kafka, AWS SQS, Other ...

What we’re looking for: Proficiency in Python (and at least one other language a plus). Experience with key libraries such as PyTorch, Pandas, Hugging Face Transformers, or similar AI toolkits. Working knowledge of common models, and their use cases and experience applying them to solve specific problems. Solid ...

data analyst or similar role. Strong SQL skills, including complex joins, aggregations and window functions. Proficiency in Python for data analysis (e.g., pandas, NumPy). Hands‐on experience with at least one cloud data platform: Databricks, AWS or Snowflake. Strong analytical and problem‐solving skills, with close attention to detail. ...

technologies is highly desirable, including PostgreSQL, MongoDB, and vector databases such as Qdrant, Milvus or pgvector. Experience with Python data-processing libraries such as Pandas or Polars is highly desirable. Nice to Have Experience working on AI or machine learning platforms. Familiarity with stream processing and event-driven architectures. Experience ...

Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) < Strong knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib) Strong software development skills (Python is the preferred language) Proven experience in deploying ML/AI services suing Kubernetes & KubeFlow Strong management ...

5+ years in applied data science, with significant experience on commercial problems (churn, LTV, propensity, attribution, pricing, or similar).* Strong SQL and Python (pandas, scikit-learn, statsmodels). Comfortable building production-grade code, not just notebooks.* Hands-on experience with Snowflake (or a comparable cloud data warehouse — BigQuery, Redshift ...

building production systems that deliver measurable business impact Technical Mastery: High proficiency in Python and SQL. Expert-level experience with the Python data stack (pandas, NumPy, scikit-learn) and at least one major ML framework (such as PyTorch or XGBoost/LightGBM) Systemic Problem Solving: Ability to work on unique ...

deploy Machine Learning capabilities and techniques into other systems. Familiarity with the Python data science stack through exposure to libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit‐learn Take pride in writing clean, reusable, maintainable and well‐tested code A desire to learn and embrace new and emerging ...

performance optimisation Networking Nice to have: 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 in scientific computing with other ...