Ampstek
Quantitative Developer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Quantitative Developer for a 12-month contract in Canary Wharf, offering hybrid work. Key skills required include Python, Pandas, NumPy, SQL, REST APIs, and version control with Git. Experience in data manipulation and software engineering best practices is essential.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
Unknown
-
🗓️ - Date
November 8, 2025
🕒 - Duration
More than 6 months
-
🏝️ - Location
Hybrid
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
London Area, United Kingdom
-
🧠 - Skills detailed
#GIT #HTML (Hypertext Markup Language) #REST (Representational State Transfer) #SQL (Structured Query Language) #Version Control #Pandas #Programming #Libraries #Unit Testing #Documentation #Pytest #Data Cleaning #Data Manipulation #NumPy #Plotly #REST API
Role description
Role: Software Engineer
Location: Canary Wharf
Project Site: Hybrid
Contract: 12 months
Responsibilities:
• Functions, classes, and object-oriented programming
• List comprehensions, generators, error handling
• Working with virtual environments and package management (pip, venv)
• Data Manipulation & Analysis (Pandas & NumPy)
• Key libraries: pandas, numpy (optional: polars)
• Data cleaning and preprocessing, handling missing values, grouping, merging, pivoting, aggregations, and SQL
• Software Engineering Best Practices
• Version control with Git
• Writing modular, reusable code
• Unit testing (e.g., pytest)
• Code documentation and docstrings
• Using linters and formatters
• Customizing with Plotly Graph Objects for advanced interactivity
• Creating dashboards with Dash: Callbacks, Layouts (HTML & CSS integration), Components (Dropdowns, sliders, graphs, tables)
• REST APIs: Fetching or sending data to backend services
Role: Software Engineer
Location: Canary Wharf
Project Site: Hybrid
Contract: 12 months
Responsibilities:
• Functions, classes, and object-oriented programming
• List comprehensions, generators, error handling
• Working with virtual environments and package management (pip, venv)
• Data Manipulation & Analysis (Pandas & NumPy)
• Key libraries: pandas, numpy (optional: polars)
• Data cleaning and preprocessing, handling missing values, grouping, merging, pivoting, aggregations, and SQL
• Software Engineering Best Practices
• Version control with Git
• Writing modular, reusable code
• Unit testing (e.g., pytest)
• Code documentation and docstrings
• Using linters and formatters
• Customizing with Plotly Graph Objects for advanced interactivity
• Creating dashboards with Dash: Callbacks, Layouts (HTML & CSS integration), Components (Dropdowns, sliders, graphs, tables)
• REST APIs: Fetching or sending data to backend services
