1 to 25 of 386 Pandas Jobs

collaborative workflows Awareness of secure development practices and experience handling sensitive or regulated data (e.g. GDPR, ISO 27001, or similar) Technical Skills Python (essential) – pandas, NumPy, and the modern data/ML ecosystem SQL – advanced querying, modelling, and optimisation Data pipelines & orchestration – Airflow, Prefect, Dagster, or dbt Data warehouses/ ...

Statistics, Physics, or related); Master's degree preferred. Professional software development experience, with deep expertise in Python and its data/engineering ecosystem (e.g., pandas, NumPy, FastAPI, orchestration tools). Proven track record of delivering production-grade automation, data pipelines, or testing frameworks in a complex enterprise environment; financial services ...

years of applied experience building production Python systems, including web/API services (Flask or FastAPI) and the ML/NLP ecosystem (scikit-learn, pandas, NumPy, spaCy, PyTorch or TensorFlow). Demonstrated experience taking machine learning models from prototype to production - training, packaging, deployment, monitoring, retraining, and decommissioning - in real ...

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 ...

with structured, semi-structured, or unstructured data, especially large-scale text or content datasets. Familiarity with common data science and ML tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib. The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions. Strong analytical thinking ...

data warehouses, lakehouse environments or analytics tools such as Power BI. Familiarity with modern data engineering frameworks and tools (e.g. Spark/PySpark, Pandas, orchestration tools). Experience with cloud data platforms on AWS or Azure (e.g. Databricks, Redshift, Microsoft Fabric). Understanding of software engineering fundamentals, including Git, testing ...

years as a Data Scientist, Hands-on experience deploying ML models to production, not just research-level familiarity, Strong proficiency in Python (NumPy, pandas, scikit-learn, matplotlib, pytorch), Understanding of Windows or Linux software development platforms Excellent command of English – both written and spoken (international client communication, presentations), Expertise ...

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 ...

DynamoDB, DocumentDB, MongoDB. Demonstrated expertise in unit testing and tools such as JUnit, Mockito, PyTest, and Selenium. Strong working knowledge of the PyData stack—pandas, NumPy for data manipulation; Jupyter Notebooks for experimentation; matplotlib/Seaborn for basic visualisation, and experience with data analysis and troubleshooting data‐related issues. Knowledge ...

scientists, and product managers Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence Required Skills & Qualifications Strong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) Experience building data pipelines and working with structured and unstructured data Solid understanding of SQL and relational and non-relational databases ...

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 ...

scientists, and product managers Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence Required Skills & Qualifications Strong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) Experience with React (hooks, state management, component architecture) Experience building data pipelines and working with structured and unstructured data Solid understanding ...

years of applied experience building production Python systems, including web/API services (Flask or FastAPI) and the ML/NLP ecosystem (scikit-learn, pandas, NumPy).Demonstrated experience taking machine learning models from prototype to production - training, packaging, deployment, monitoring, retraining, and decommissioning - in real-world business applications. Experience with ...

models What We’re Looking For: Essential Skills & Experience Proven experience solving complex, real-world problems using data science and analytics Strong Python skills (pandas, numpy, scikit-learn) with a solid grounding in probability and statistics Deep understanding of machine learning methods and their practical application Experience delivering multiple ...

models What We’re Looking For: Essential Skills & Experience Proven experience solving complex, real-world problems using data science and analytics Strong Python skills (pandas, numpy, scikit-learn) with a solid grounding in probability and statistics Deep understanding of machine learning methods and their practical application Experience delivering multiple ...

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 ...

engineering fundamentals: working with Parquet, Hive-partitioned datasets, and SQL against large tables (Athena/Presto). Solid working knowledge of the PyData stack — pandas and NumPy for data manipulation, Jupyter for experimentation, matplotlib/Seaborn for visualisation — and experience troubleshooting data-quality issues. Testing discipline with PyTest ...

Docker and Kubernetes for scalable production systemsFamiliarity with distributed computing frameworks (e.g., Spark, Dask), cloud platforms (e.g., AWS, Azure, GCP), and analytics libraries (e.g., pandas, numpy, matplotlib)Exposure to DevOps, DataOps, and MLOps concepts and best practicesExperience with core technologies such as Python, PySpark, SQL, Airflow, Databricks, Kedro, Dask/ ...

pipelines in a professional setting (e.g., internship) is a plusAbility to write clean, maintainable, scalable, and robust code in PythonFamiliarity with analytics libraries (e.g., pandas, numpy, matplotlib), distributed computing frameworks (e.g., Spark, Dask), and cloud platforms (e.g., AWS, Azure, GCP)Basic understanding or exposure to containerization technologies such as Docker ...

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 ...

sequential modelingExcellent communication skills with the ability to communicate concepts clearly and preciselyExperience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) databases; and iii) cloud platform services (AWS, GCP, Azure)NICE TO HAVESExperience as a Data Architect or Senior ManagerProven track record of deploying ...

using Python and SQL, including data manipulation, exploratory analysis, statistics, and visualization. Working knowledge of Python data-science libraries and analytic environments such as pandas, NumPy, SciPy, scikit-learn, Matplotlib/Plotly, Jupyter, or equivalent tools. Experience translating mission, operational, or engineering questions into measurable analytic approaches, identifying appropriate data ...

Working You’ll work in a modern data and machine learning environment. The role is likely to involve: Python, including libraries such as Pandas, NumPy and scikit‐learn. SQL and large structured datasets. Cloud data platforms such as Snowflake, Databricks or similar. Git‐based version control and code review. ...

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/ ...