151 to 175 of 235 NumPy Jobs

results Providing relevant insights Advanced statistical and analytical techniques and concepts sampling methods, Regression Properties of distributions Weighting sample-based data Statistical tests proper usage Real-world applications. Python - NumPy, SciPy, Pandas, MLlib, scikit-learn, and other common data and machine learning related libraries Working knowledge of SQL, data structures and databases (Snowflake - desirable) This is a pragmatic and humble More ❯

in system release cycles, post-trade analysis, and incident reviews to drive continuous improvement and operational resilience. Required Skills & Experience Strong Python skills, including scripting and data analysis (Pandas, NumPy). Advanced SQL experience (PostgreSQL or similar) working with large, real-time datasets. Proven Linux system administration experience, including shell scripting, process monitoring, and performance optimization in low-latency or More ❯

in system release cycles, post-trade analysis, and incident reviews to drive continuous improvement and operational resilience. Required Skills & Experience Strong Python skills, including scripting and data analysis (Pandas, NumPy). Advanced SQL experience (PostgreSQL or similar) working with large, real-time datasets. Proven Linux system administration experience, including shell scripting, process monitoring, and performance optimization in low-latency or More ❯

Strong understanding of OOP principles, functions, classes, list comprehensions, generators, and exception handling. Experience managing virtual environments and dependencies using pip or venv. Data Manipulation & Analysis: Proficiency with Pandas , NumPy (and optionally Polars). Strong data cleaning, transformation, grouping, merging, and aggregation skills. Experience with SQL for data querying. Software Engineering Best Practices: Experience with Git for version control. Writing More ❯

retail, or distribution environment. High proficiency in SQL and Excel for data extraction and manipulation. Experience using Power BI or Tableau for dashboards and visualisation. Familiarity with Python (pandas, numpy) for advanced analytics and automation. Commercially focused mindset with the ability to connect data to business impact. Confident communicator who can explain complex insights to non-technical audiences. Experience working More ❯

Build scalable data pipelines and APIs Ideal Candidate Will Have: Previous experience as a Data Scientist or Data Engineer Strong command of Python (including libraries such as scikit-learn, NumPy, matplotlib) Experience in deep learning frameworks such as TensorFlow or PyTorch Knowledge of SQL and relational databases; experience with Big Data environments Familiarity with API development and NoSQL databases Understanding More ❯

Build scalable data pipelines and APIs Ideal Candidate Will Have: Previous experience as a Data Scientist or Data Engineer Strong command of Python (including libraries such as scikit-learn, NumPy, matplotlib) Experience in deep learning frameworks such as TensorFlow or PyTorch Knowledge of SQL and relational databases; experience with Big Data environments Familiarity with API development and NoSQL databases Understanding More ❯

scalable machine learning models and training workflows using PyTorch or TensorFlow. Develop and maintain end-to-end ML pipelines, from data preprocessing to model deployment. Leverage the Python ecosystem (NumPy, pandas, scikit-learn, spaCy, NLTK, Hugging Face Transformers) for feature engineering, model development, and evaluation. Manage and track machine learning experiments using MLflow, ensuring reproducibility, versioning, and lifecycle management. Collaborate More ❯

processes. What skills should I have? As our Data Scientist you will have: At least 2 years experience in Statistics and Machine Learning Experience with Python Machine Learning libraries (NumPy, Pandas, SKLearn etc) At least 3 years Python programming experience Experience applying models to Big Data Familiar with the principles of Continuous Integration and Deployment (CI/CD) Familiar with More ❯

What skills should I have? As our Senior Data Scientist you will have: At least 4 years experience in Statistics and Machine Learning Experience with Python Machine Learning libraries (NumPy, Pandas, SKLearn etc) At least 3 years Python programming experience Experience applying models to Big Data Familiar with the principles of Continuous Integration and Deployment (CI/CD) Familiar with More ❯

initiatives, including price, volume, and mix analysis and margin optimisation . Tech Environment Core Skills: SQL (essential), Power BI (advantageous) Platform: Microsoft Fabric (mid-implementation) Languages: Python (pandas/numpy - desirable, not essential) Other: Salesforce & Google Analytics exposure beneficial About You Proven experience as an Insight Analyst , ideally in wholesale, distribution, or another product-heavy industry. Strong knowledge of pricing More ❯

initiatives, including price, volume, and mix analysis and margin optimisation . Tech Environment Core Skills: SQL (essential), Power BI (advantageous) Platform: Microsoft Fabric (mid-implementation) Languages: Python (pandas/numpy - desirable, not essential) Other: Salesforce & Google Analytics exposure beneficial About You Proven experience as an Insight Analyst , ideally in wholesale, distribution, or another product-heavy industry. Strong knowledge of pricing More ❯

setting? Were looking for a talented OPS Engineer to join our growing teams in Erskine or Newcastle. Key Responsibilities Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines More ❯

and non-technical stakeholders. Stay ahead of the curve by experimenting with emerging AI and ML techniques. What You’ll Bring Strong background in Python or R (e.g., Pandas, NumPy, Scikit-learn, TensorFlow). Skilled in SQL and statistical analysis. Proven experience in data science, ideally within energy, optimisation, or IoT-focused applications. Solid grasp of machine learning techniques such More ❯

engineers and T&L domain experts Required Skills/Experience The ideal candidate will have the following: Be an expert Python programmer proficient in frameworks/libraries such as: Numpy, Pandas, Scikit-Learn, Langchain, Llamaindex, Azure AI Foundry amongst others. Must have Azure and be an expert with R&D on generative AI techniques Practical experience with GenAI techniques such More ❯

load data in various data stores like RDBMS, Oracle, S3, PL/SQL, and/or shared drives. 9. Solid experience in Python and libraries such as Panda/NumPy, etc. or Spark 10. Demonstrable experience developing scripting in Linux and Windows 11. Experience with migrating applications to AWS (Cloud) will be an added advantage 12. Knowledge of Cloud computing More ❯

Google Analytics, conversion optimisation Skills & Experience Essential Strong SQL proficiency for data extraction and transformation Advanced Excel (pivot tables, VLOOKUPs, formulas) Power BI or Tableau experience Python familiarity (pandas, numpy) Proven data or BI role background Experience with large, complex datasets History of delivering practical insights Strong communication skills Desirable Wholesale/distribution/supply chain experience ERP systems exposure More ❯

production-grade analytics platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll use 🌳 Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/ More ❯

production-grade analytics platforms for sensitive environments. Collaborate across engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll use 🌳 Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud: CI/ More ❯

ArcGIS), remote sensing techniques, and the application of data science in the IC. Expert proficiency in Python (or similar languages) and experience with data science libraries (TensorFlow, PyTorch, Pandas, NumPy). Strong experience with big data processing tools (e.g., Spark, Hadoop, AWS or Azure cloud platforms). Expertise in working with geospatial data formats (e.g., GeoTIFF, Shapefiles, WMS, WFS) and More ❯

building and orchestrating ML models for Computer Vision tasks Technical Stack : You are highly proficient in Python and expert in relevant ML frameworks (PyTorch, TensorFlow/Keras) and packages (NumPy, Pandas) Data Skills : Preferably, you have hands on experience with data science tooling and expertise in dataset curation, analysis, and cleaning for ML training Code Quality : You write high quality More ❯

or MATLAB. Understanding of Convolutional Neural Networks (CNNs) and Feature Extraction techniques. Basic knowledge of programming languages including Python, C++, and C, along and libraries such as Scikit-Learn, NumPy, and/or SciPy . Your Package & Perks: A competitive salary Flexible working hours 32 days holiday, (including public Holidays) plus the opportunity to earn up to an extra More ❯

or MATLAB. Understanding of Convolutional Neural Networks (CNNs) and Feature Extraction techniques. Basic knowledge of programming languages including Python, C++, and C, along and libraries such as Scikit-Learn, NumPy, and/or SciPy . Your Package & Perks: A competitive salary Flexible working hours 32 days holiday, (including public Holidays) plus the opportunity to earn up to an extra More ❯

learning or deep learning (thesis, research projects, internships, or substantial personal projects) Excellent Python skills with experience using core AI/ML libraries (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Experience training, tuning, and evaluating models using real datasets (not just toy examples), including careful validation and error analysis Familiarity with modern LLM tooling and workflows (e.g. using APIs, building More ❯

learning or deep learning (thesis, research projects, internships, or substantial personal projects) Excellent Python skills with experience using core AI/ML libraries (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Experience training, tuning, and evaluating models using real datasets (not just toy examples), including careful validation and error analysis Familiarity with modern LLM tooling and workflows (e.g. using APIs, building More ❯