26 to 50 of 170 Permanent NumPy Jobs

Mandatory required high proficiency in ETL, SQL and database management Experience with AWS services like Glue, Athena, Redshift, Lambda, S3 Python programming experience using data libraries like pandas and numpy etc Interest in machine learning, logistic regression and emerging solutions for data analytics You are comfortable working without direct supervision on outcomes that have a direct impact on the business More ❯

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 ❯

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 ❯

approach to working in cross-functional Agile squads. Your experience: Expert-level fluency in Python (required) with deep experience in ML, OR, and DS libraries (e.g. scikit-learn, pandas, numpy, Gurobi). Strong knowledge of machine learning and optimisation techniques-including supervised, unsupervised learning, and operations research methods. Solid background in software engineering for data science products: version control (Git More ❯

structured and unstructured datasets of varying sizes. Track record of implementing impactful models that drive sustained business results. Proficiency in the Python data science tech stack (pandas, scikit-learn, NumPy, and visualisation libraries) Experience working in a Linux-based cloud environment (e.g. GCP, Azure, AWS). Experience using git version control. Communication, stakeholder management, and problem-solving skills are critical. More ❯

industry settings, such as financial forecasting, operations optimisation, or customer segmentation. Comfortable with key ML frameworks (such as Scikit-learn, TensorFlow, PyTorch, Hugging Face) and data manipulation tools (Pandas, NumPy), as well as version control, containerisation, and ML deployment pipelines. Understands how to apply MLOps principles in production environments To be successful in this role you must have hands-on More ❯

your technical capabilities in a collaborative environment, this is an excellent opportunity to take the next step in your career. Essential Solid programming knowledge with Python Experience using Pandas, NumPy, Matplotlib, and PyTorch Strong understanding of SQL for querying and data manipulation Familiarity with CI/CD workflows and Git version control Detail-oriented and proactive problem solver Enthusiastic about More ❯

6+ years of hands-on experience in developing and deploying machine learning or AI systems in production environments in financial services. Proficiency in Python and essential libraries (e.g., Pandas, NumPy, TensorFlow, PyTorch, PySpark). Solid foundation in software engineering best practices, including modular code design, version control, and documentation. Excellent communication and collaboration skills, with the ability to work across More ❯

with customer stakeholders to align on requirements and technical implementations Required Qualifications: Active Poly Minimum 3-5 years' experience with: Data Processing Python Libraries such as PySpark, Pandas and Numpy Experience with API development in Python using Python libraries such as FastAPI Experience with Unit Testing Frameworks in PyTest and Mocking Desired Qualifications: Experience with Python ORM tools for database 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 ❯

years of work experience in software developement ( Python and C++ )- Academic degree in computer science, mechatronics, electronic engineering, telecommunication engineering or similar qualification, PhD welcome- Experience with Python (numpy/scipy/matplotlib)- Hands-on experience in AWS- Software debugging skills, understanding of performance optimization- Very good understanding of the software development process, preferably in the automotive area- You are More ❯

Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience coaching and reviewing work of junior team members. Strong Python skills (pandas, numpy, scikit-learn) and a solid grounding in probability and statistics. Deep knowledge of machine learning methods and their practical application. Experience managing multiple end-to-end data science projects across More ❯

Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience coaching and reviewing work of junior team members. Strong Python skills (pandas, numpy, scikit-learn) and a solid grounding in probability and statistics. Deep knowledge of machine learning methods and their practical application. Experience managing multiple end-to-end data science projects across 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 ❯

t always work on our data so you will need to understand how to develop your own models • Strong programming skills and experience working with Python, Scikit-Learn, SciPy, NumPy, Pandas and Jupyter Notebooks is desirable. Experience with object-oriented programming is beneficial • Publications at top conferences, such as NeurIPS, ICML or ICLR, is highly desirable Why should you apply 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 Experience with transformer LLMs - attractive, nice to have Cloud (AWS) deployments and monitoring, basic networking and 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 ❯

Effectively manage technical priorities, meet deadlines, and deliver on project objectives. Masters degree in a STEM field (maths, science, engineering etc.) or equivalent Strong programming skills in Python (e.g., NumPy, Pandas, scikit-learn, TensorFlow/PyTorch). Demonstrable experience in creating and developing Python libraries. Demonstrable experience designing, implementing and training machine learning models from scratch. Strong foundations in applied 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 ❯

skills with experience building complex, maintainable systems Professional software development experience with a track record of delivering high-quality, production-grade code Experience with scientific computing libraries such as NumPy, Pandas, or SciPy in production environments Holistic software development mindset covering testing, documentation, security, and performance Track record of mentoring other engineers and sharing knowledge across teams Working knowledge of More ❯

skills with experience building complex, maintainable systems Professional software development experience with a track record of delivering high-quality, production-grade code Experience with scientific computing libraries such as NumPy, Pandas, or SciPy in production environments Holistic software development mindset covering testing, documentation, security, and performance Track record of mentoring other engineers and sharing knowledge across teams Desirable: Working knowledge More ❯

with Python and Django on an increasingly more service-oriented architecture. The rest of the tech stack includes Django REST Framework, PostgreSQL, AWS, React.js, Kubernetes, Docker, Redis, Celery, Pandas, Numpy, Git, Jenkins, and Elasticsearch. We have a very large but clean code base as we put significant emphasis on design patterns, code readability, automated testing, maintainability, and extendability. Responsibilities Work More ❯

React Router, MaterialUI, GitHub actions, on an increasingly more service-oriented architecture. The rest of the tech stack include Django REST Framework, PostgreSQL, AWS, Kubernetes, Docker, Redis, Celery, Pandas, Numpy, Github, Jenkins, Elasticsearch and lots of raw SQL for analytics. We have a very large but clean code base as we put significant emphasis on design patterns, code readability, testability 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 ❯