51 to 75 of 210 Pandas Jobs in England

tools (Airflow, Prefect, Temporal) or have built custom pipeline systems for multi-step autonomous processes. You bridge science and engineering. You are comfortable with scientific computing libraries (NumPy, SciPy, pandas) and understand scientific literature formats, databases (PubMed, arXiv), and academic data processing. What Sets You Apart: You have a research background. You are a former academic researcher who transitioned to More ❯

the adoption of best practices in data science across the organisation, lead other data science engineers MINIMUM QUALIFICATIONS Industry experience using Python for data science (e.g. numpy, scipy, scikit, pandas, etc.) and SQL or other languages for relational databases. Experience with a cloud platform such as (AWS, GCP, Azure etc.) Experience with common data science tools; statistical analysis, mathematical modelling More ❯

with experience building complex, maintainable systems Professional software development experience with a track record of delivering high-quality, production-grade code Experience with scientific computing libraries such as NumPy, Pandas, or SciPy in production environments Holistic software development mindset covering testing, documentation, security, and performance Track record of mentoring other engineers and sharing knowledge across teams Working knowledge of mathematical More ❯

with experience building complex, maintainable systems Professional software development experience with a track record of delivering high-quality, production-grade code Experience with scientific computing libraries such as NumPy, Pandas, or SciPy in production environments Holistic software development mindset covering testing, documentation, security, and performance Track record of mentoring other engineers and sharing knowledge across teams Desirable: Working knowledge of More ❯

We expect this team to work across multiple technologies around a core, including Python, AWS (EKS, S3, Lambda, CDK, etc.), AI/ML/Data Science libraries (LLM tooling, pandas, etc.) About Role: We are hiring several Software Engineers of differing levels to build AI capabilities through the delivery of AI-powered features within PatentSight+ and internal AI tools. PatentSight+ More ❯

Query, React Router, MaterialUI, GitHub actions, on an increasingly more service-oriented architecture. The rest of the tech stack include Django REST Framework, PostgreSQL, AWS, Kubernetes, Docker, Redis, Celery, Pandas, Numpy, Github, Jenkins, Elasticsearch and lots of raw SQL for analytics. We have a very large but clean code base as we put significant emphasis on design patterns, code readability More ❯

or data engineering. Ability to work standard European time-zone hours and legal authorisation to work in your country of residence. Strong experience with Python's data ecosystem (e.g., Pandas, NumPy) and deep expertise in SQL for building robust data extraction, transformation, and analysis pipelines. Hands-on experience with big data processing frameworks such as Apache Spark, Databricks, or Snowflake More ❯

work with Python and Django on an increasingly more service-oriented architecture. The rest of the tech stack include Django REST Framework, PostgreSQL, AWS, React.js, Kubernetes, Docker, Redis, Celery, Pandas, Numpy, Git, Jenkins and Elasticsearch. We have a very large but clean code base as we put significant emphasis on design patterns, code readability, automated testing, maintainability and extendability. Responsibilities More ❯

track record of handling high-visibility, customer-facing outputs. 1+ years experience using Python (or another programming language e.g. R, C++, Java) and with the scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.) Familiarity with renewable energy technologies, market design, and regulatory frameworks within European power markets, specifically GB, Germany, Spain, Portugal, France, or Italy. Experience writing technical, report-style More ❯

track record of handling high-visibility, customer-facing outputs. 1+ years experience using Python (or another programming language e.g. R, C++, Java) and with the scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.) Familiarity with renewable energy technologies, market design, and regulatory frameworks within European power markets, specifically GB, Germany, Spain, Portugal, France, or Italy. Experience writing technical, report-style More ❯

Data Engineering & Modelling: Understanding of ORM/entity relationships, NoSQL, JSON, XML, SQL and exposure to data visualisation tools (ETL/ELT). Data Science Tools: Proficiency in Numpy, Pandas, Matplotlib, Seaborn and Scikit-learn. MLOps: Experience building pipelines (CI/CD) using Bicep or similar technologies. Expertise in deploying, monitoring and managing machine learning models in production environments. API More ❯

Hands-on experience with OpenAI APIs and Microsoft Azure AI services. Strong understanding of large language models, prompt engineering, and fine-tuning techniques. Experience with data manipulation libraries (e.g., Pandas, NumPy) and cloud platforms. Familiarity with MLOps, version control (e.g., Git), and deployment tools (e.g., Docker, Kubernetes). Excellent problem-solving skills and the ability to work on complex AI More ❯

meaningful insights from structured and unstructured datasets of varying sizes. Track record of implementing impactful models that drive sustained business results. Proficiency in the Python data science tech stack (pandas, scikit-learn, NumPy, and visualisation libraries) Experience working in a Linux-based cloud environment (e.g. GCP, Azure, AWS). Experience using git version control. Communication, stakeholder management, and problem-solving More ❯

in designing and implementing efficient data pipelines, including performance tuning and optimization. Proven ability to apply machine learning techniques to real-world problems. Familiarity with core libraries such as Pandas, NumPy, Scikit-learn, SciPy, and Polars is expected. Experience with digital signal processing, mobile sensor physics, or behavioural signal design. Proven track record of designing and delivering scalable data products More ❯

Understanding of customer experience principles and marketing analytics including customer journey mapping, conversion optimization, and media effectiveness. Proficiency in Python with extensive experience in data science libraries (e.g.scikit-learn, pandas, NumPy, SciPy, etc) Experience with ML frameworks such as TensorFlow, PyTorch, XGBoost, LightGBM, or similar Strong SQL skills and experience with data warehousing solutions (Snowflake, BigQuery, Redshift) Experience with cloud More ❯

some of the biggest names in private equity. Ideal Candidate Experience: 5+ years in data science roles, preferably in fast-moving or early-stage environments Languages & Tools: Strong Python (Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch) Advanced SQL AWS MLOps tooling (e.g., MLflow, SageMaker, or similar) Bonus Points For: Knowledge of LLMs, RAG pipelines, prompt engineering, or agentic interfaces Experience More ❯

some of the biggest names in private equity. Ideal Candidate Experience: 5+ years in data science roles, preferably in fast-moving or early-stage environments Languages & Tools: Strong Python (Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch) Advanced SQL AWS MLOps tooling (e.g., MLflow, SageMaker, or similar) Bonus Points For: Knowledge of LLMs, RAG pipelines, prompt engineering, or agentic interfaces Experience More ❯

highly advanced analytical tools. Company: Trust in Soda Qualifications: Essential Requirements: Extensive experience in deploying products Solid experience with Python, and associated libraries such as scipy, scikit-learn and pandas/numpy Experience creating NLP/DL/RNN models Experience with Image Processing and CNNs Excellent communication skills Degree in CS, maths, statistics, engineering, physics or similar Desirable Requirements More ❯

experience working with consumer behaviour data—ideally within healthcare, digital health, or related B2C environments Strong programming skills in Python, with experience using libraries like scikit-learn, XGBoost, and pandas Practical experience in MLOps or strong knowledge of model deployment (e.g. MLflow, Airflow, Docker, Kubernetes, model monitoring tools) Familiarity with cloud environments (AWS, GCP, or Azure) and data pipelines Excellent More ❯

experience working with consumer behaviour data—ideally within healthcare, digital health, or related B2C environments Strong programming skills in Python, with experience using libraries like scikit-learn, XGBoost, and pandas Practical experience in MLOps or strong knowledge of model deployment (e.g. MLflow, Airflow, Docker, Kubernetes, model monitoring tools) Familiarity with cloud environments (AWS, GCP, or Azure) and data pipelines Excellent More ❯

fresh ideas to the team. Skills and Experience: Degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Proficiency in Python and key libraries such as NumPy, Pandas, scikit-learn, TensorFlow or PyTorch. Basic understanding of machine learning algorithms and model evaluation techniques. Strong analytical and communication skills. Comfortable working in a collaborative environment and taking feedback. Desirable More ❯

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 ❯

has: 🎓 A degree in Data Science, Mathematics, Computer Science, Statistics, or a related field. 🧠 Solid understanding of data analysis, machine learning concepts, and statistical methods. 🐍 Proficiency in Python (e.g., Pandas, Scikit-learn, NumPy) or R, with exposure to tools like Jupyter, SQL, or cloud platforms (e.g., AWS, GCP). 📊 Experience working with data—through academic projects, internships, or personal work More ❯

has: 🎓 A degree in Data Science, Mathematics, Computer Science, Statistics, or a related field. 🧠 Solid understanding of data analysis, machine learning concepts, and statistical methods. 🐍 Proficiency in Python (e.g., Pandas, Scikit-learn, NumPy) or R, with exposure to tools like Jupyter, SQL, or cloud platforms (e.g., AWS, GCP). 📊 Experience working with data—through academic projects, internships, or personal work More ❯

order to apply for the position of Quantitative Developer - Python, you'll need to meet the following criteria: Strong Python skills (for example 5+ years), including libraries like NumPy, Pandas, Polars. Experience in C++ and scripting (e.g., Bash) is a plus. Background in equities/equity derivatives trading. Problem-solving mindset, comfortable in a fast-paced, collaborative environment. Degree in More ❯