performance, and scalability. Qualifications Bachelor’s Degree in Computer Science, Information Systems, Mathematics, etc. 7+ years in Python and libraries like PyTorch, NumPy, Pandas, Matplotlib, QuantLib, etc Experience in Systems that handle high-throughput, low-latency data Experience with multi-threading, concurrency, and high-frequency trading (HFT). Experience with more »
The experience you’ll bring to the team: - Proficiency in Python, including ML/DL frameworks (e.g., Scikit-learn, TensorFlow) and visualization libraries (e.g., Matplotlib, Seaborn). - Strong SQL skills and experience with data visualization tools (e.g., Tableau). - Basic statistical analysis knowledge. - Experience in deploying production ML systems. - Familiarity more »
experience at a top tier hedge fund, proprietary trading house or investment bank Exposure to pandas, numpy, scikit-learn, statsmodels-tsa, TensorFlow, Keras, and Matplotlib libraries more »
Birmingham, England, United Kingdom Hybrid / WFH Options
Digital Waffle
used in Machine Learning and Data Science such as TensorFlow, PyTorch, and scikit-learn. Data Science and Visualisation libraries including Pandas, NumPy, scikit-learn, matplotlib, Seaborn. Cloud services used in machine learning and data science, such as Azure, OpenAI, Hugging Face, AWS ML/AI. Machine Learning Applications development life more »
XGBoost) and modern deep learning algorithms (e.g., BERT, LSTM). Strong knowledge of SQL and Python's data analysis ecosystem (Jupyter, Pandas, Scikit-Learn, Matplotlib). Advanced Techniques : Familiarity with ensemble methods like bagging and boosting. Understanding of model evaluation, data pre-processing techniques (standardisation, normalisation, handling missing data). more »
in Computer Science, Mathematics, Statistics, Business Administration, or related field. Advanced knowledge of SQL and Python, including popular Data Science packages such as pandas, matplotlib, seaborn, numpy, and sklearn. Familiarity with machine learning algorithms and techniques, with a deep understanding of their underlying principles. Strong problem-solving skills and meticulous more »
knowledge of statistical packages and ML/DL libraries/frameworks (e.g., Scikit-learn, NumPy, Keras/TensorFlow/PyTorch) and visualization libraries (e.g., Matplotlib, Plotly, Seaborn). Database Skills: Fluency in SQL and familiarity with data visualization tools (e.g., DataStudio, Tableau). Statistical Analysis: Basic understanding of statistical analysis. more »
knowledge of statistical packages and ML/DL libraries/frameworks (e.g., Scikit-learn, NumPy, Keras/TensorFlow/PyTorch) and visualization libraries (e.g., Matplotlib, Plotly, Seaborn). Database Skills: Fluency in SQL and familiarity with data visualization tools (e.g., DataStudio, Tableau). Statistical Analysis: Basic understanding of statistical analysis. more »
The experience you'll bring to the team: - Proficiency in Python, including ML/DL frameworks (e.g., Scikit-learn, TensorFlow) and visualization libraries (e.g., Matplotlib, Seaborn). - Strong SQL skills and experience with data visualization tools (e.g., Tableau). - Basic statistical analysis knowledge. - Experience in deploying production ML systems. - Familiarity more »
