11 of 11 Pandas Jobs in Wakefield

Key Skills & Experience: 5+ years of relevant industry experience, ideally within financial services, capital markets, or asset management sectors. Proficient in Python 3, including pandas, GeoPandas, boto3, Pydantic, and Data Version Control (DVC). Familiar with Django 4 and core API development. Strong hands-on experience with AWS cloud infrastructure More ❯

Science, Engineering, or a related field (or equivalent practical experience). Technical Skills: Deep expertise in Python, including libraries such as Django, Flask, FastAPI, Pandas and NumPy. Strong knowledge of relational and non-relational databases (e.g., PostgreSQL, MongoDB, Redis). Proficiency with cloud platforms (e.g., AWS, Azure, GCP) and containerization More ❯

driven architectures Clear communicator with experience writing technical documentation Comfortable working with Agile, TOGAF, or similar frameworks Desirable: Experience with Python and data libraries (Pandas, Scikit-learn) Knowledge of ETL tools (Airflow, Talend, NiFi) Familiarity with analytics platforms (SAS, Posit) Prior work in high-performance or large-scale data environments More ❯

reliability and cost, or improving our search service Tech Stack: Platform: AWS, Pulumi, Docker, Prefect, Github actions, Grafana cloud monitoring Data Science: Python, PyTorch, Pandas, Spacy, Huggingface, Numpy, Streamlit, Argilla, Weights and Biases Backend: Python, FastAPI, PostgreSQL, Vespa, SQLAlchemy, AWS Batch, Lambda, S3 Frontend: React, Next.js Key skills and experience More ❯

building and implementing forecasting models using modern ML techniques. Deep understanding of time series analysis, statistics, and forecasting methodologies. Production-level Python programming skills (Pandas, Polars, Scikit-learn, NumPy, SciPy). Comfort working in a collaborative, cross-functional environment. Please note, this role cannot offer sponsorship at this stage More ❯

technology on highly visible and large-scale projects. What you’ll bring to the role Strong grounding in ML approaches, techniques and frameworks Python, Pandas, Tensor Flow, Scikit-learn, Numpy, SciPy Experience deploying to the cloud and working with Azure (Azure DevOps, Azure ML, Azure SQL, ADF etc.) Able to More ❯

experience with Oracle, SQL Server, and PostGres SQL databases. Technical Skills: Proficiency in at least 2 of the following: SQL, PSQL, C#, Python and Pandas for data manipulation and analysis. Problem Solving: Detail-oriented with exceptional problem-solving skills, capable of troubleshooting issues quickly and efficiently. Communication: Excellent ability to More ❯

we like to see from you: Cloud & Infrastructure: Cloud platform expertise for multi-tenant systems. Ideas for scalable architecture with DevOps. Programming: Python prowess (pandas, FastAPI, Pydantic). Git mastery. API and database skills (e.g., PostgreSQL). ML/AI: ML model training and deployment expertise. AutoML know-how (e.g. More ❯

making. Required Qualifications: Basic knowledge of Python and/or SQL. Interest in data analytics, statistics, or machine learning. Familiarity with tools like Excel, Pandas, Numpy, or visualization libraries. Strong communication and time management skills. Preferred (Not Mandatory): Previous coursework, projects, or online certifications in data science. Understanding of data More ❯

communication and organizational skills. Preferred (Not Mandatory): Exposure to data visualization tools like Tableau, Power BI, or Looker. Experience with Python for data analysis (Pandas, Matplotlib, etc.). Academic or personal projects involving data analytics or reporting. Knowledge of statistical concepts or business KPIs. Who Can Apply: Students or recent More ❯

accessed in the most efficient and effective manner. Your Toolkit The Languages You Speak : Python, SQL, the dialect of data. Libraries Tools : Terraform, Flask, Pandas, FastAPI, Dagster, GraphQL, SQLAlchemy, GitLab, Athena. Your Trusted Companions : Docker, Snowflake, MongoDB, Relational Databases (eg MySQL, PostgreSQL), Dagster, Airflow/Luigi, Spark, Kubernetes. Your AWS … CI/CD) automation, rigorous code reviews, documentation as communication. Preferred Qualifications Familiar with data manipulation and experience with Python libraries like Flask, FastAPI, Pandas, PySpark, PyTorch, to name a few. Proficiency in statistics and/or machine learning libraries like NumPy, matplotlib, seaborn, scikit-learn, etc. Experience in building More ❯