Data Manipulation & Analysis: Proficient in data manipulation and analysis using tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau to communicate insights effectively. Our offer: Cash: Depends on experience Equity: Generous equity package, on a standard vesting schedule Impact & Exposure: Work More ❯
TensorFlow, PyTorch, scikit-learn) Solid understanding of statistical analysis and predictive modeling techniques Experience working with large datasets and data visualization tools (e.g., Tableau, Matplotlib, Seaborn) Excellent problem-solving skills and the ability to communicate complex ideas effectively to stakeholders Advanced degree (Master's or Ph.D.) in Data Science, Statistics More ❯
proficiency in data manipulation libraries (e.g., Pandas, NumPy). Experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow) and data visualization tools (e.g., Tableau, Matplotlib). Solid understanding of statistics, probability, and data-driven decision-making. Experience working with databases (SQL) and data warehousing solutions. Strong problem-solving skills and More ❯
the ability to clean and transform data in preparation for analysis or modelling. Data visualisation - using tools like Power BI, Tableau, or libraries like Matplotlib or Seaborn to tell stories. Statistical analysis - understanding of key statistics and distributions, hypothesis testing, and the ability to derive insights. Working with both structured More ❯
ability to analyze and interpret large datasets, uncovering meaningful trends and insights. You are proficient in SQL and experienced in using Python (pandas, numpy, matplotlib, seaborn) for exploratory data analysis and data visualization. Big plus is practical familiarity with the big data stack (Spark, Presto/Athena, Hive). You More ❯
models, clustering algorithms, classification models and time series techniques in a production environment. Proficiency with Python and all related Data Science libraries (numpy, pandas, matplotlib, etc.), and SQL with excellent analytical and algorithmic skills. A proven record for successful implementation of translating business requirements into a technical solution. Multi-tasking More ❯
a STEM field. Proven experience in timeseries data analysis, statistical techniques and data visualisation. Expertise in Python data science stack including Pandas, Numpy, Spark, matplotlib, Jupyter. SQL experience is a plus. Experience with ETL and evaluation of large datasets. Working knowledge of Snowflake, Linux/UNIX, Git, Jira is preferable. More ❯
data analysis and visualization a meticulous coder with an eye for readability, with experience in python and industry standard data science packages (numpy, pandas, matplotlib, sqlite, or others). Able to use SQL syntax writing and workflows. You have good familiarity with file/data formats, such as markdown, json More ❯
algorithms for power grid problems on top of standard optimization libraries. Familiarity with data science libraries such as NumPy, Pandas, and visualization tools (e.g., Matplotlib, Seaborn). Experience with cloud computing platforms (e.g., Google Cloud Platform, AWS, Azure) and containerization technologies (e.g., Docker, Kubernetes). Experience contributing to open-source More ❯
algorithms for power grid problems on top of standard optimization libraries. Familiarity with data science libraries such as NumPy, Pandas, and visualization tools (e.g., Matplotlib, Seaborn). Experience with cloud computing platforms (e.g., Google Cloud Platform, AWS, Azure) and containerization technologies (e.g., Docker, Kubernetes). Experience contributing to open-source More ❯
extracting insights from heterogeneous multi-dimensional datasets. Ability to apply machine learning techniques (e.g., scikit-learn, PyTorch, TensorFlow) and present complex data visually using Matplotlib, seaborn, or Streamlit. Fluent in Python, with experience working with data processing libraries such as Pandas. Strong SQL skills, a good understanding of Linux, parallel More ❯
a STEM field. Proven experience in timeseries data analysis, statistical techniques and data visualisation. Expertise in Python data science stack including Pandas, Numpy, Spark, matplotlib, Jupyter. SQL experience is a plus. Experience with ETL and evaluation of large datasets. Working knowledge of Snowflake, Linux/UNIX, Git, Jira is preferable. More ❯
business needs and translate them into data-driven solutions. Create insightful visualizations and dashboards using tools like Tableau, Power BI, or Python libraries (e.g., Matplotlib, Seaborn) to communicate findings effectively to non-technical stakeholders. Continuously evaluate and improve the performance of models through cross-validation, hyperparameter tuning, and other techniques. … data manipulation and transformation tools such as Pandas, NumPy, and SQL for working with large datasets. Expertise in creating impactful visualizations using tools like Matplotlib, Seaborn, Tableau, or Power BI. Familiarity with big data tools and platforms like Hadoop, Spark, or cloud-based tools (e.g., AWS, Google Cloud, Azure). More ❯
developing and deploying machine learning models in production. Strong programming skills in Python and SQL. Proficiency with data visualization tools (e.g., Tableau, Power BI, matplotlib) and cloud platforms (preferably AWS). Expertise in statistics and machine learning frameworks (e.g., PyTorch, scikit-learn). Familiarity with Git and collaborative workflows, such More ❯
a team with fast turnarounds, manage workloads effectively and readily assume additional responsibilities Exposure to data analysis libraries (e.g., pandas, numpy) and visualisation tools (Matplotlib, plotly) Understanding software testing principles and frameworks Preferred skills Knowledge of financial instruments and equity markets Familiarity with cloud services Familiarity with quantitative research methodologies More ❯
collaborating with team members. Knowledge of CI/CD pipelines (e.g. GitHub Actions) is a plus. Experience with data visualization tools and libraries (e.g., Matplotlib, Seaborn, Tableau, Power BI). Experience with cloud services (e.g., AWS, Google Cloud Platform, Azure) for data storage and processing. Ability to work with cross More ❯
or related quantitative field. Minimum of 2+ years of Python developer proficiency with quantitative analysis experience with packages such as numpy, pandas, scipy, scikitlearn, matplotlib, etc. Proficiency in Linux environment (including shell scripting). 1+ years of experience with automation frameworks in software testing (e.g., PyTest, Cucumber). Experience and More ❯
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 a More ❯
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 a More ❯
cases. Effective technical communication, able to advocate for solutions and explain them clearly to non-experts. Proficient in Python, including libraries like pandas, PyTorch, matplotlib, and Seaborn, with experience in data science and engineering. Experience with cloud service technologies and enterprise tools such as Databricks, Snowflake, AWS Bedrock, SageMaker, Azure More ❯
role in the financial markets Solid understanding of financial markets and products – ideally equities Strong Python skills including data analysis libraries and visualization tools (Matplotlib, Plotly, pandas, numpy) Strong understanding of software development lifecycle and practices including CI/CD Degree or Masters in Engineering, Computer Science, Mathematics or related More ❯
work through others. Experienced in using Python and SQL to query and analyse large datasets, with expertise in libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn for data manipulation, statistical analysis, and visualisation. Familiarity with Monte Carlo simulations in Python and/or PyMC3 for Bayesian modelling is a More ❯
work through others. Experienced in using Python and SQL to query and analyse large datasets, with expertise in libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn for data manipulation, statistical analysis, and visualisation. Familiarity with Monte Carlo simulations in Python and/or PyMC3 for Bayesian modelling is a More ❯
work through others. Experienced in using Python and SQL to query and analyse large datasets, with expertise in libraries such as Pandas, NumPy, SciPy, Matplotlib, and Seaborn for data manipulation, statistical analysis, and visualisation. Familiarity with Monte Carlo simulations in Python and/or PyMC3 for Bayesian modelling is a More ❯
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 and their More ❯
