stakeholders to deliver impactful solutions. Ensure data quality, security, and governance. About You Experience in analytics or model/data engineering. Advanced Python skills (Numpy/Pandas). Strong SQL and relational database design expertise. Excellent communication skills. Benefits £6,000 per annum training & conference budget to help you up More ❯
Wakefield, Yorkshire, United Kingdom Hybrid / WFH Options
Flippa.com
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 ETL/ELT processes and data pipelines with platforms like Airflow, Dagster, or Luigi. What's important More ❯
and large-scale data warehouses (Snowflake, Redshift, Presto). Proficiency in data visualization tools (Databricks, PowerBI) and the Python data science ecosystem (Jupyter, Pandas, Numpy, Matplotlib). Plusses: Financial services background Degree in cybersecurity Any advanced Data bricks qualifications Have lead teams of more than 10 people Recent involvement in More ❯
and large-scale data warehouses (Snowflake, Redshift, Presto). Proficiency in data visualization tools (Databricks, PowerBI) and the Python data science ecosystem (Jupyter, Pandas, Numpy, Matplotlib). Plusses: Financial services background Degree in cybersecurity Any advanced Data bricks qualifications Have lead teams of more than 10 people Recent involvement in More ❯
be 100% hands-on, with the opportunity to step into a leadership role as the team scales. Tech Stack - Python, FastAPI, AWS, Typescript, PostgreSQL, NumPy, Pandas What You’ll Be Doing - Designing, building, and maintaining scalable backend systems for AI-driven healthcare solutions. Working closely with the ML engineers to More ❯
and large-scale data warehouses (Snowflake, Redshift, Presto). Proficiency in data visualization tools (Databricks, PowerBI) and the Python data science ecosystem (Jupyter, Pandas, Numpy, Matplotlib). Plusses: Financial services background Degree in cybersecurity Any advanced Data bricks qualifications Have lead teams of more than 10 people Recent involvement in More ❯
and large-scale data warehouses (Snowflake, Redshift, Presto). Proficiency in data visualization tools (Databricks, PowerBI) and the Python data science ecosystem (Jupyter, Pandas, Numpy, Matplotlib). Plusses: Financial services background Degree in cybersecurity Any advanced Data bricks qualifications Have lead teams of more than 10 people Recent involvement in More ❯
Skills & Experience: 5+ years of experience in Python development, ideally within financial services Strong knowledge of Python frameworks (e.g. Flask, Django), data libraries (Pandas, NumPy) Cloud-native experience, especially Microsoft Azure (Functions, Data Lake, etc.) Familiarity with DevOps practices (Git, CI/CD, testing frameworks) Experience with SQL/NoSQL More ❯
Skills & Experience: 5+ years of experience in Python development, ideally within financial services Strong knowledge of Python frameworks (e.g. Flask, Django), data libraries (Pandas, NumPy) Cloud-native experience, especially Microsoft Azure (Functions, Data Lake, etc.) Familiarity with DevOps practices (Git, CI/CD, testing frameworks) Experience with SQL/NoSQL More ❯
experience in developing and deploying AI solutions in a business environment. Proficiency in Python and familiarity with AI frameworks and libraries such as Pandas, NumPy, PyTorch, Scikit-Learn, Streamlit, and SciPy. Strong understanding of software development principles, AI engineering, and MLOps. Experience working with cloud-based AI solutions on platforms More ❯
GCP) to store and process data. Document workflows, pipelines, and transformation logic for transparency. Key Skills & Experience: Strong hands-on experience in Python (Pandas, NumPy, PySpark). Experience building ETL/ELT processes. Familiarity with cloud platforms (AWS, Azure, GCP) and big data technologies (e.g., Snowflake, Databricks). Understanding of More ❯
as profiling and debugging and understanding of system performance and scalability - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. PREFERRED QUALIFICATIONS - Experience with popular deep learning frameworks such as MxNet and Tensor Flow. - PhD More ❯
Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing RESTful More ❯
preferably) FX markets - over the last 3-5 years - in an investment context. Fluent in Python 3.11+, the standard library, and external libraries like numpy, pandas, matplotlib, and scikit-learn. Confident in SQL Server or similar; experience with Azure and Docker is a positive. An understanding of machine learning processes More ❯
and deployment. Strong software engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). More ❯
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 More ❯
and a good understanding of software engineering principles and clean code practices. Expert-level knowledge of Python for machine learning and data manipulation (pandas, NumPy). Advanced experience with SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning More ❯
as profiling and debugging and understanding of system performance and scalability Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. PREFERRED QUALIFICATIONS Experience with popular deep learning frameworks such as MxNet and Tensor Flow. PhD Amazon is an equal opportunities employer. We believe More ❯
of engagements; advisory, design & implementation. Contribute to internal initiatives such as blogs & technical forums. Requirements Substantial experience with Python and relevant libraries (e.g. Pandas, Numpy, Scikit Learn, PyTorch, Tensorflow). Experience driving ML & data science solutions into production. You can put the numbers into a business perspective - you're a More ❯
Markets, Particularly Oil, Gas, and Commodities. Business Analysis Skills including requirements gathering, process mapping, and data analysis. Experience with SQL, C#.Net, Git, Python (Panda, Numpy, ML libraries), and data visualization tools such as Power BI or Tableau. Benefits & perks Competitive salary Vitality health insurance and dental cover 38 days of More ❯
practices Experience with cloud technologies (AWS, Azure, or GCP) Solid understanding of financial markets and risk concepts Experience with data processing and analysis libraries (NumPy, Pandas) Nice to Have Experience with financial risk management systems or trading platforms Knowledge of quantitative finance or financial mathematics Familiarity with CI/CD More ❯
london, south east england, united kingdom Hybrid / WFH Options
Hunter Bond
practices Experience with cloud technologies (AWS, Azure, or GCP) Solid understanding of financial markets and risk concepts Experience with data processing and analysis libraries (NumPy, Pandas) Nice to Have Experience with financial risk management systems or trading platforms Knowledge of quantitative finance or financial mathematics Familiarity with CI/CD More ❯
some of the following skills: Machine learning techniques - including supervised and unsupervised methods and model evaluation. Key libraries including scikit-learn, scipy, pandas, and numpy (or equivalents). Data preprocessing - working with large untidy datasets and the ability to clean and transform data in preparation for analysis or modelling. Data More ❯
/B testing, entity extraction, and feature engineering. Proficiency in programming languages such as Python, R, and SQL, and data analysis libraries (e.g., Pandas, NumPy, SciPy, Tidyverse). Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, NLTK). Experience with NLP techniques, such as named More ❯
