51 to 75 of 240 Pandas Jobs

Understanding/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 More ❯

monitoring into production systems, using tools such as Datadog, Grafana, Prometheus Experience designing tight SLO (>0.99) workflows on scheduling systems at scale (e.g. AirFlow) Expert-level programmer in Python, Pandas and SQL (Snowflake and Postgres) Superb code-review skills and strong instincts on how to write robust, maintainable, and generalizable code Nice to have, but not required Parallel computing patterns More ❯

collaboratively in a team setting Eagerness to continuously learn and adapt to evolving tools, stacks, and requirements Nice-to-Have: Exposure to data analysis libraries or scientific computing (e.g., pandas, NumPy, matplotlib, Py-Torch, Tensor-flow, SK-Learn) Basic understanding of machine learning principles or experience with small academic projects Familiarity with cloud platforms (AWS/GCP/Azure), APIs More ❯

collaboratively in a team setting Eagerness to continuously learn and adapt to evolving tools, stacks, and requirements Nice-to-Have: Exposure to data analysis libraries or scientific computing (e.g., pandas, NumPy, matplotlib, Py-Torch, Tensor-flow, SK-Learn) Basic understanding of machine learning principles or experience with small academic projects Familiarity with cloud platforms (AWS/GCP/Azure), APIs More ❯

Essential 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 More ❯

Essential 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 More ❯

serving infrastructure, utilising technologies such as Kafka, Python, Docker, Apache Flink, Airflow, and Databricks. Actively assist in model development and debugging using tools like PyTorch, Scikit-learn, MLFlow, and Pandas, working with models from gradient boosting classifiers to custom GPT-based solutions. gain a deep understanding of Simply Business's wider data ecosystem to build efficient and scalable machine learning More ❯

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 corporate More ❯

stakeholders in a compelling and actionable way Mentor junior data scientists and contribute to the evolution of data science standards and practices Key Skills & Technologies Technical: Strong in Python (pandas, scikit-learn, XGBoost, LightGBM, etc.) Proficient in SQL for complex customer data extraction and manipulation Experience with customer analytics techniques: segmentation, RFM analysis, clustering, time-series, A/B testing More ❯

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? • Highly More ❯

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 security More ❯

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 present More ❯

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 mathematics More ❯

stakeholders in a compelling and actionable way Mentor junior data scientists and contribute to the evolution of data science standards and practices Key Skills & Technologies Technical: Strong in Python (pandas, scikit-learn, XGBoost, LightGBM, etc.) Proficient in SQL for complex customer data extraction and manipulation Experience with customer analytics techniques: segmentation, RFM analysis, clustering, time-series, A/B testing More ❯

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 transitioned to More ❯

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 analysis, mathematical modelling More ❯

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 mathematical More ❯

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 of More ❯

Query, 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 More ❯

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 of More ❯

work with Python and Django on an increasingly more service-oriented architecture. The rest of the tech stack include 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 More ❯

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-style More ❯

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-style More ❯

end-to-end delivery skills, including model deployment and operationalisation, with a solid grasp of MLOps best practices. Proficient in Python and key data science libraries such as NumPy, Pandas, Scikit-learn, PyTorch, and Statsmodels. Solid academic background in mathematics, computer science, or a related field, ideally with an MSc or PhD Practical experience with cloud platforms (preferably GCP), Agile More ❯

Data Engineering & Modelling: Understanding of ORM/entity relationships, NoSQL, JSON, XML, SQL and exposure to data visualisation tools (ETL/ELT). Data Science Tools: Proficiency in Numpy, Pandas, Matplotlib, Seaborn and Scikit-learn. MLOps: Experience building pipelines (CI/CD) using Bicep or similar technologies. Expertise in deploying, monitoring and managing machine learning models in production environments. API More ❯