Requirements: Minimum of 5 years of hands-on experience in machine learning engineering. Proven expertise in regression modelling and time series modelling. Numpy/Pandas/Keras/Tensorslow/XGBoost/Scikit-learn Experienced in GCP preferably Extensive background in deploying and productionizing machine learning models. Strong programming skills more »
of the sport (rules, terminology, insight). Proficiency in Python. Experience using relational databases and SQL. Familiarity with data manipulation and analysis libraries (e.g., pandas, numpy, jupyter, scikit-learn). Knowledge of machine learning and statistical methods (e.g. linear/logistic regression, decision trees, random forest, unsupervised methods) is preferred. more »
optimizers, super/unsupervised learning, feature engineering, etc.). Strong experience with Python required understanding of the ML/DS frameworks (XGBoost, Scikit-learn, Pandas, Numpy, etc.), and modular/modern OOP software design practices with a modern ML/Data/Cloud engineering technical stack If you’re interested more »
developing AI-based products Experience of developing using Computer Vision 3+ years of experience implementing and/or architecting MLOps solutions Python (NumPy, PyTorch, Pandas, etc.), Demonstrable leadership experience in managing a team of 4+ individuals Experience of working within a start-up would be beneficial but not an essential more »
where appropriate and ensuring best practices and understood and followed. Technical Skills and Qualifications Expert knowledge in python including libraries/frameworks such as pandas, numpy, pyspark Good understanding of OOP, software design patterns, and SOLID principles Good experience in Docker Good experience in Linux Good experience in Airflow Good more »
control, and debugging. Experience of mentoring and supporting development of junior engineers. Data Analysis and Processing: Skilled in analytics, data manipulation with frameworks like Pandas and PySpark. Architectural Proficiency: Deep understanding of data architecture, modelling, and warehousing concepts, coupled with experience in big data technologies and distributed computing. Cloud and more »
Fixed Income instruments Build order execution and order management improvements Improve and refine back office systems Requirements: Strong Python coding skills with experience in Pandas and Numpy BSc in CompSci or similar STEM subject Strong version control, testing and continuous integration. Good SQL Skills. For more information, please can you more »
Working Arrangements: Hybrid (2-3 days p/w in office) Salary: £120,000 – £130,000 Industry: Consultancy/Finance Tech Stack: Python, SQL, Pandas, Numpy 👩🏻💻 Great opportunity for a talented Developer (Python, SQL, Pandas, Numpy) to join a tech consultancy that deliver greenfield platforms for their clients. The Company … banks in the world, they operate across the globe and a renowned household name. The Role ✨ They are seeking a skilled Developer (Python, SQL, Pandas, Numpy) to join a Front Office equity trading team. This is a great opportunity to join a Front Office team (Python, SQL, Pandas, Numpy), working … directly on design and architecture and overseeing the scalability of infrastructure. Desired Skills ⚙️ Python (Django or FastAPI a plus but not a requirement) SQL Pandas, Numpy Postgres, MongoDB Benefits 🏖 10% matched pension Health Insurance If you are a skilled Developer (Python, SQL, Pandas, Numpy) who is interested in this role more »
a tech team using a diverse tech stack including: Backend: Python, FastAPI, PostgreSQL, Vespa, SQLAlchemy, Flask. Frontend: React, Next.js. Data Science: Python, Jupyter, PyTorch, Pandas, Spacy, Huggingface, Numpy, Streamlit, Weights and biases. Infra: Pulumi, Docker, AWS AppRunner, Step Functions, Grafana cloud monitoring, Prefect. Who you are Must haves: Experience using more »
z2bz0 years of experience in a Data Science setting Experience in AI/Machine Learning + either PyTorch/TensorFlow Experience with NumPy/Pandas Matplotlib/Plotly SQL/MySQL/database experience The ability driving projects from conception to completion Excellent communication skills, Fluency in English is required more »
City of London, London, United Kingdom Hybrid / WFH Options
E.ON Next
in a quantitative discipline eg. Statistics, Mathematics, Physics, Machine Learning ● Deep expertise in Python (production-level) and SQL ● Proficiency in machine learning libraries (eg. Pandas, scikit-learn, TensorFlow) and experience with MLOps frameworks for model deployment ● Strong visualisation skills including experience with Tableau ● Familiarity with Git-based source control methodologies more »
Central London / West End, London, United Kingdom Hybrid / WFH Options
E.ON Next
in a quantitative discipline eg. Statistics, Mathematics, Physics, Machine Learning ● Deep expertise in Python (production-level) and SQL ● Proficiency in machine learning libraries (eg. Pandas, scikit-learn, TensorFlow) and experience with MLOps frameworks for model deployment ● Strong visualisation skills including experience with Tableau ● Familiarity with Git-based source control methodologies more »
algorithm development. Proficiency in quantitative analysis, statistical modeling, time series analysis, and data visualization. Experience with quantitative libraries and frameworks such as NumPy, SciPy, pandas, TensorFlow, or PyTorch. Familiarity with financial markets, trading instruments, and market microstructure. Strong problem-solving abilities and attention to detail, with a passion for solving more »
in machine learning methodologies and algorithms Expertise in popular data science platforms such as Alteryx and Python, including libraries and frameworks like NumPy, SciPy, Pandas, NLTK, TensorFlow, PyTorch, and Airflow Strong understanding of statistical analysis, encompassing distributions, statistical testing, regression, and other techniques Experience handling unstructured data sets Familiarity with more »
Pipelines for collection of new alternate datasets Design and Build Market Data APIs Implementation of Fundamental Trading strategies Technical Skills required – Excellent Python (inc. Pandas, NumPy, SciPy, et al) skills Experience of AWS, (Azure/GCP) beneficial 3+ years experience as a Quantitative Developer working directly with Trading and Research more »
model performance issues (using your experience of debugging models). Requirements Significant experience building and deploying ML models using the Python data stack (numpy, pandas, sklearn). Understand software engineering best practices (version control, unit tests, code reviews, CI/CD) and how they apply to machine learning engineering. Strong more »
that in mind you’ll need to have the following: Extensive software engineering/data engineering experience with Python and it's associated libraries - Pandas, Numpy, PySpark. A background in Java/C# would be beneficial to show programming aptitude. AWS, Kafka, Redis Experience within a trading technology environment would more »
demonstrated by a history of identifying and implementing automation opportunities. Experience working with a variety of data storage and manipulation tools such as SQL, Pandas, Elasticsearch & Kibana, Snowflake. Ability to recognize patterns and establish standards to streamline development and enhance reliability. Excellent interpersonal skills, enabling positive and collaborative relationships with more »
management principles. Experience with quantitative modeling techniques, including statistical analysis, machine learning, and time series analysis. Proficiency in data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib). Excellent problem-solving skills and attention to detail. Prior experience in a quantitative role at a hedge fund, proprietary trading firm, or more »
microstructure experience would be very beneficial. Proficiency in programming languages such as C++, Python or MATLAB along with experience in data analysis libraries (e.g., pandas, NumPy) and version control systems (e.g., Git). Familiarity with low-latency trading systems, high-performance computing, and algorithmic trading strategies. Strong academic background in more »
and productionalize containerized algos for deployment in hybrid cloud environments (GCP, Azure) Connect and blend data from various data sources within enterprise tools (python, pandas, or SQL) to enable application of Data Science methods Create metrics and analytical reports to ensure data quality and business value. Clean, structure and normalize more »
production at scale. Deep knowledge of machine learning algorithms applied to solving business problems. Proficiency in Python and popular Data Science frameworks (e.g. pytorch, pandas, numpy etc) and MLOps platforms (e.g. Sagemaker) Solid understanding of metrics, benchmarking and evaluation methodology AI-powered user-facing products. Experience working in highly collaborative more »
