101 to 125 of 237 NumPy Jobs

Role Requirements 2-4 years' experience in applied machine learning and generative AI, including work with large language models. Strong Python programming skills with experience in core ML libraries (numpy, pandas, scikit-learn, boosting methods). Proven ability to design, test, and deploy production-ready machine learning solutions. Hands-on experience in data processing and feature engineering for complex datasets. More ❯

Provide data-driven recommendations to improve engagement metrics Requirements Experience in Customer Marketing Data Science, including applied statistics and machine learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks Experience with ML Ops, including deployment and monitoring Ability to work cross-functionally with More ❯

Provide data-driven recommendations to improve engagement metrics Requirements Experience in Customer Marketing Data Science, including applied statistics and machine learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks Experience with ML Ops, including deployment and monitoring Ability to work cross-functionally with More ❯

Stay up-to-date with emerging trends and technologies in the field of data science. Requirements Proven experience as a data scientist using Python and a range of libraries (Numpy, Pandas, Scikit-Learn, Matplotlib, Plotly etc.). Strong expertise in statistical modelling, machine learning, and data mining techniques. Data engineering (pipelines, databases, infrastructure), ideally with AWS experience would be an More ❯

experience applying statistics and data science in a commercial setting. Proven track record in customer or marketing analytics - understanding acquisition, engagement, churn, and lifetime value. Proficiency in Python (Pandas, NumPy, Scikit-learn, Statsmodels) for data wrangling, analysis, and modelling. Ability to communicate complex findings in a clear, business-relevant way. Experience working collaboratively in agile, cross-functional teams. Please note More ❯

experience applying statistics and data science in a commercial setting. Proven track record in customer or marketing analytics - understanding acquisition, engagement, churn, and lifetime value. Proficiency in Python (Pandas, NumPy, Scikit-learn, Statsmodels) for data wrangling, analysis, and modelling. Ability to communicate complex findings in a clear, business-relevant way. Experience working collaboratively in agile, cross-functional teams. Please note More ❯

For: Essential: Experience with LLMs (GPT, BERT) and NLP tasks. Fine-tuning pre-trained models for domain-specific applications. Strong Python skills (OOP, PyTorch, Hugging Face, scikit-learn, Pandas, NumPy). Deploying models with Docker, Kubernetes, or serverless platforms. Familiarity with CI/CD, MLOps, and cloud platforms (AWS preferred). Desirable: Named entity recognition, recommendation systems, or image analysis. More ❯

For: Essential: Experience with LLMs (GPT, BERT) and NLP tasks. Fine-tuning pre-trained models for domain-specific applications. Strong Python skills (OOP, PyTorch, Hugging Face, scikit-learn, Pandas, NumPy). Deploying models with Docker, Kubernetes, or serverless platforms. Familiarity with CI/CD, MLOps, and cloud platforms (AWS preferred). Desirable: Named entity recognition, recommendation systems, or image analysis. More ❯

setting up CI/CD pipelines using tools like Azure DevOps, GitHub Actions, or GitLab CI, targeting Azure environments. Experience with popular Python libraries and frameworks such as Pandas, NumPy, and PySpark. Benefits Full-time, permanent contract. Competitive salary up to £60,000 per annum, depending on experience. Hybrid working model based in Aberdeen (2 days per week in the More ❯

in the UK, and further abroad internationally. Skills And Experience Required Python experience Be great to have a web framework – Flask, FastAPI, Django, etc Data manipulation with Pandas/numpy SQL Server Salary - Up to £56,000 dependent on experience. Hybrid - Flexible 3 days in the office (London SE1 9SG) They are passionate about transforming data into powerful insights that More ❯

with modern data platforms and cloud technologies. Key Responsibilities: Develop, test, and deploy scalable data engineering solutions using Python . Build and maintain data pipelines leveraging libraries such as NumPy, pandas, BeautifulSoup, Selenium, pdfplumber, and Requests . Write and optimize complex SQL queries and manage databases including PostgreSQL . Integrate and automate workflows using DevOps tools (e.g., CI/CD More ❯

with modern data platforms and cloud technologies. Key Responsibilities: Develop, test, and deploy scalable data engineering solutions using Python . Build and maintain data pipelines leveraging libraries such as NumPy, pandas, BeautifulSoup, Selenium, pdfplumber, and Requests . Write and optimize complex SQL queries and manage databases including PostgreSQL . Integrate and automate workflows using DevOps tools (e.g., CI/CD More ❯

to teams adopting AI tooling. What Youll Bring 5+ years in software/ML engineering, ideally with production deployment experience. Strong Python background, comfortable across data frameworks like Pandas, NumPy, SciPy, Dask, Polars, or PySpark. Proven experience setting up ML pipelines, integrating with AWS/Databricks, and applying CI/CD principles. Solid understanding of time-series forecasting and supervised More ❯

teams adopting AI tooling. What You’ll Bring • 5+ years in software/ML engineering, ideally with production deployment experience. • Strong Python background, comfortable across data frameworks like Pandas, NumPy, SciPy, Dask, Polars, or PySpark. • Proven experience setting up ML pipelines, integrating with AWS/Databricks, and applying CI/CD principles. • Solid understanding of time-series forecasting and supervised More ❯

complete the above-mentioned tasks: Experience with machine learning techniques and algorithms, including k-NN, Naive Bayes, SVM, and Decision Forests; Experience with data science toolkits, including R, Weka, NumPy, and MatLab; Experience with data visualization tools, including D3.js and GGplot; Experience using query languages, including SQL, Hive, and Pig; Experience with NoSQL databases, including MongoDB, Cassandra, and HBase; Experience More ❯

into data workflows, unlocking even more potential from their datasets. Skills & Experience Strong Python experience Experience with a web framework – Flask, FastAPI, Django , etc. Solid understanding of Pandas/NumPy for data manipulation SQL Server experience Experience building or maintaining web scraping tools to collect and structure data from online sources Who this role is great for Early-career Python More ❯

implement basic AI algorithms and explore practical applications of AI. Overview of AI and Machine Learning Types of machine learning (supervised, unsupervised, reinforcement) Introduction to Python Libraries for AI - NumPy, Pandas, Matplotlib Scikit-learn for machine learning Building AI Models Data preprocessing Training and evaluating models Advanced Programming for AI Integration This programme aims to equip participants with the knowledge More ❯

concept to production deployment. Skills & Experience Advanced Python skills with a focus on numerical computing and performance. Experience with AI inference acceleration (e.g., TensorRT, ONNX Runtime) and libraries like NumPy, CuPy, SciPy. Expertise in hardware-accelerated video encoding/decoding using Python. Strong communication skills and ability to write maintainable, well-documented code. Self-starter with proven ability to lead More ❯

Exposure to cloud deployments (AWS preferred). Familiarity with MQTT, ZMQ, WebRTC, MIDI, or similar communication protocols. Experience building backend components, APIs, or control-plane systems. Desirable: FFMPEG, PyQt, NumPy, SQLAlchemy experience. Understanding of secure communications (SSL/TLS, JWT). Passion for scalable, highly available architecture (real-time or mission-critical systems). Why Apply? Join a highly technical More ❯

related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Familiarity with cloud platforms (AWS, Azure, or GCP) and basic distributed systems concepts Strong problem-solving mindset with a passion for building practical, scalable AI solutions Excellent teamwork and communication More ❯

related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Familiarity with cloud platforms (AWS, Azure, or GCP) and basic distributed systems concepts Strong problem-solving mindset with a passion for building practical, scalable AI solutions Excellent teamwork and communication More ❯

into production-ready features Contributing to both R&D-heavy and commercially driven engineering initiatives What you can bring Strong Python skills, including experience with data processing libraries (e.g. Numpy, Pandas). Bonus: RasterIO or other geospatial tooling experience. Experience with AWS and containerised environments (Docker). Familiarity with backend frameworks (FastAPI, Flask, or Django). Experience working with data More ❯

into production-ready features Contributing to both R&D-heavy and commercially driven engineering initiatives What you can bring Strong Python skills, including experience with data processing libraries (e.g. Numpy, Pandas). Bonus: RasterIO or other geospatial tooling experience. Experience with AWS and containerised environments (Docker). Familiarity with backend frameworks (FastAPI, Flask, or Django). Experience working with data More ❯

experience delivering data migration or integration projects , ideally with ERP/CRM systems such as Microsoft Dynamics . Strong technical skills in Python , including libraries such as Pandas and NumPy . Hands-on experience with ETL design, data warehousing, and relational databases (SQL). Advanced proficiency in SQL and data modelling techniques. Knowledge of cloud data platforms (Azure preferred, AWS More ❯

in MLOps implementation for deploying, monitoring, and managing ML models in production environments. Proficiency in Python and experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy Strong understanding of cloud technologies and AI/ML platforms, particularly AWS SageMaker. Solid grasp of software engineering principles including design patterns, testing, CI/CD, security, and version control More ❯