management or mentorship. Have good communication skills. Nice to have Experience deploying LLMs and agent-based systems Our technology stack Python and associated ML/DS libraries (scikit-learn, numpy, pandas, LightGBM, LangChain/LangGraph, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, ECR, Athena, etc. MLOps: Terraform, Docker, Spacelift, Airflow, MLFlow Monitoring: New Relic CI/CD: Jenkins, Github More ❯
in Computer Science, Engineering, or a related field (or equivalent practical experience). A Master's degree is preferred Very good knowledge of Python language and statistical libraries like Numpy, Pandas, Polars Minimum 5 years experience in Python development Strong problem-solving skills and the ability to work in a fast-paced, collaborative and geographically distributed environment Excellent communication and More ❯
mitigation strategies. Design, develop, and implement quantitative models to assess Value at Risk (VaR), portfolio sensitivities, and other market risk metrics. Utilize Python programming language and relevant libraries (Pandas, NumPy, SciPy) to manipulate, analyze, and visualize market data. Build and maintain data pipelines for efficient ingestion, transformation, and cleansing of financial data from various sources. Conduct back-testing and stress … Master's degree in Computer Science, Mathematics, Finance, or a related field. Strong understanding of market risk principles and methodologies, including econometrics. Proficiency in Python and relevant libraries (Pandas, NumPy, SciPy). Solid understanding of time series analysis techniques and statistical modeling. Experience with building and maintaining data pipelines for financial data. Excellent communication and collaboration skills. Ability to work More ❯
AWS Data Science Tools: Hands-on with SageMaker, Lambda, Step Functions, S3, Athena. - OCR Development: Experience with Amazon Textract, Tesseract, and LLM-based OCR. - Python Expertise: Skilled in Pandas, NumPy, scikit-learn, PyTorch, Hugging Face Transformers; modular, testable code. - ML Models: Proficient in regression, classification, clustering, and time-series forecasting. - Business Insight: Translate business needs into data-driven solutions and More ❯
/experience analyzing US Treasury and/or European government bond markets preferred Strong proficiency in Python programming and data manipulation libraries and experience dealing with datasets (e.g., Pandas, NumPy, SciPy) Experience with Dash/Plotly or other visualization software highly desirable Experience with database programming languages (e.g. kdb, SQL) Strong knowledge of MS Excel (especially using real-time data More ❯
SQL for data mining; additional experience and knowledge of Big Data tools preferred. Excellent Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualisation and API libraries (matplotlib, plotly, streamlit, Flask, etc). Understanding of Gen AI models, Vector databases, Agents, and follow the More ❯
SQL for data mining; additional experience and knowledge of Big Data tools preferred. Excellent Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualisation and API libraries (matplotlib, plotly, streamlit, Flask, etc). Understanding of Gen AI models, Vector databases, Agents, and follow the More ❯
procedures, and query optimization) • Proven experience with at least one major BI platform (prefer QuickSight) including dashboard creation and maintenance • Proficiency in Python, particularly with data analysis libraries (pandas, numpy, scikit-learn) • Experience automating data collection and reporting processes • Demonstrated ability to translate business requirements into technical solutions PREFERRED QUALIFICATIONS • Experience with cloud platforms (AWS) • Proficiency in statistical analysis and More ❯
transparent environment, engaging with the whole investment process Preferred Technical Skills Expert in Python and/or KDB/Q Proficient in modern data science tools stacks (Jupyter, pandas, numpy, sklearn) with machine learning experience Good understanding of using Slurm or similar parallel computing tools Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related STEM field More ❯
alignment, etc.) Experience with molecular property prediction and multi-objective optimization using machine learning and/or deep learning methods Experienced with common python toolkits for scientific computing (e.g., numpy, pandas, scipy), machine learning (e.g., scikit-learn, pytorch), and cheminformatics/bioinformatics (e.g., rdkit, openeye, biotite, biopython) Familiarity running simulations and training models on high-performance computing (GPU) environments for More ❯
both a technical and non-technical audience Independent and self-driven learner, able to step outside of their area of expertise Python; we work with asyncio, SQLAlchemy, FastAPI, Pydantic, NumPy, Pandas SQL; performance tuning, schema design, monitoring in production, we mainly work with PostgreSQL Cloud (AWS) deployments and monitoring, basic networking and security best practices Command line familiarity, git, automated More ❯
instruction of established Quant Analytics team. What You Will Bring • University degree or equivalent with proven and displayed competency in data interrogation. • Strong proficiency and experience in Python (e.g., NumPy, pandas, scikit-learn) and quantitative thinking - you enjoy working with data to unearth patterns, trends, and nuances. • Exceptional analytical, problem-solving, and communication skills, with the ability to translate and More ❯
both a technical and non-technical audience Independent and self-driven learner, able to step outside of their area of expertise Python; we work with asyncio, SQLAlchemy, FastAPI, Pydantic, NumPy, Pandas SQL; performance tuning, schema design, monitoring in production, we mainly work with PostgreSQL Cloud (AWS) deployments and monitoring, basic networking and security best practices Command line familiarity, git, automated More ❯
workflow orchestration tools (Airflow, Prefect, Temporal) or have built custom pipeline systems for multi-step autonomous processes. You bridge science and engineering. You are comfortable with scientific computing libraries (NumPy, SciPy, pandas) and understand scientific literature formats, databases (PubMed, arXiv), and academic data processing. What Sets You Apart: You have a research background. You are a former academic researcher who More ❯
specific challenges Drive the adoption of best practices in data science across the organisation, lead other data science engineers MINIMUM QUALIFICATIONS Industry experience using Python for data science (e.g. numpy, scipy, scikit, pandas, etc.) and SQL or other languages for relational databases. Experience with a cloud platform such as (AWS, GCP, Azure etc.) Experience with common data science tools; statistical More ❯
a track record of handling high-visibility, customer-facing outputs. 1+ years experience using Python (or another programming language e.g. R, C++, Java) and with the scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.) Familiarity with renewable energy technologies, market design, and regulatory frameworks within European power markets, specifically GB, Germany, Spain, Portugal, France, or Italy. Experience writing technical, report More ❯
data engineering. Ability to work standard European time-zone hours and legal authorisation to work in your country of residence. Strong experience with Python's data ecosystem (e.g., Pandas, NumPy) and deep expertise in SQL for building robust data extraction, transformation, and analysis pipelines. Hands-on experience with big data processing frameworks such as Apache Spark, Databricks, or Snowflake, with More ❯
a track record of handling high-visibility, customer-facing outputs. 1+ years experience using Python (or another programming language e.g. R, C++, Java) and with the scientific computing stack (Numpy, Pandas, SciPy, ScikitLearn, etc.) Familiarity with renewable energy technologies, market design, and regulatory frameworks within European power markets, specifically GB, Germany, Spain, Portugal, France, or Italy. Experience writing technical, report More ❯
Machine Learning Engineer - SaaS - London (Tech stack: Machine Learning Engineer, Python, TensorFlow, PyTorch, scikit-learn, Keras, Natural Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, ONNX (Open Neural Network Exchange) We have several exciting … training will be provided to fill any gaps in your skill set): Machine Learning Engineer, Python, TensorFlow, PyTorch, scikit-learn, Keras, Natural Language Processing (NLP), Hugging Face Transformers, Pandas, NumPy, Jupyter Notebooks, Matplotlib, Seaborn, Flask (for building APIs), FastAPI, Docker, MLflow, DVC (Data Version Control), AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform, TensorFlow Serving, ONNX (Open Neural Network More ❯
drift, response quality and spend; implement automated retraining triggers. Collaboration - work with Data Engineering, Product and Ops teams to translate business constraints into mathematical formulations. Tech stack Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow) SQL (Redshift, Snowflake or similar) AWS SageMaker → Azure ML migration, with Docker, Git, Terraform, Airflow/ADF Optional extras: Spark, Databricks, Kubernetes. What you'll … optimisation/recommender work at production scale (dynamic pricing, yield, marketplace matching). Mathematical optimisation know-how - LP/MIP, heuristics, constraint tuning, objective-function design. Python toolbox: pandas, NumPy, scikit-learn, PyTorch/TensorFlow; clean, tested code. Cloud ML: hands-on with AWS SageMaker plus exposure to Azure ML; Docker, Git, CI/CD, Terraform. SQL mastery for heavy More ❯
Deployment: ship a model as a container, update an Airflow (or Azure Data Factory) job. Review: inspect dashboards, compare control vs. treatment, plan next experiment. Tech stack Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow) SQL (Redshift, Snowflake or similar) AWS SageMaker → Azure ML migration, with Docker, Git, Terraform, Airflow/ADF Optional extras: Spark, Databricks, Kubernetes. What you'll … optimisation/recommender work at production scale (dynamic pricing, yield, marketplace matching). Mathematical optimisation know-how - LP/MIP, heuristics, constraint tuning, objective-function design. Python toolbox: pandas, NumPy, scikit-learn, PyTorch/TensorFlow; clean, tested code. Cloud ML: hands-on with AWS SageMaker plus exposure to Azure ML; Docker, Git, CI/CD, Terraform. SQL mastery for heavy More ❯
someone who is not only technically strong, but solution-oriented, strategically minded, and able to communicate insights clearly to both technical and non-technical audiences. Requirements: Advance Python (Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch) & SQL skills. (Snowflake a plus) Experience with Data warehousing and database technologies Solid machine learning experience (modelling to deployment) Cloud exposure (GCP/AWS/ More ❯
analytical tools. Company: Trust in Soda Qualifications: Essential Requirements: Extensive experience in deploying products Solid experience with Python, and associated libraries such as scipy, scikit-learn and pandas/numpy Experience creating NLP/DL/RNN models Experience with Image Processing and CNNs Excellent communication skills Degree in CS, maths, statistics, engineering, physics or similar Desirable Requirements: NoSQL databases More ❯
findings Skills Proficiency in data analytics, including statistics, visualization, and handling large datasets Basic understanding of TCP and UDP network protocols Experience with Python and data libraries like Pandas, Numpy/Scipy Familiarity with modern computer systems and networks Experience with real-time exchange market data and order entry is a plus Profile Degree in Data Analytics or related field More ❯
degree in Computer Science, Mathematics, Physics, Engineering, or a related field. Programming Proficiency: Strong programming skills in Python and must be comfortable with common dataset libraries e.g. pandas, polars, numpy, duckdb etc. Quantitative Skills: Solid understanding of quantitative finance and statistical methods. Trading Knowledge: Familiarity with the trading process and financial markets. System Design: Experience in designing and implementing high More ❯
