176 to 200 of 457 Pandas Jobs

AI-driven initiatives, including text and sentiment analysis Collaborating closely with Data Engineering and BI to deliver robust, end-to-end ML pipelines and model monitoring Tech Environment: Python (pandas, scikit-learn, modern ML frameworks) SQL for analysis and model input preparation Cloud environment (AWS/GCP/Azure) Exposure to NLP, MLOps, or CI/CD pipelines is a More ❯

and modelling skills, including time series and ensemble models. Experience in manipulating and interpreting data from disparate sources. Proficient in Python coding and core data science libraries, such as Pandas, TensorFlow, Scikit-learn etc. Ideally previous experience with Snowflake and DBT. Experience with Cloud Computing (AWS, GCP, Azure) - Ideally in AWS. Creativity and innovative thinking to explore diverse data sources More ❯

Technical & Analytical Skills Hands-on experience with large data sets and data profiling. Proficiency in data tools: Power BI, Excel, SQL, Python, Databricks. Familiarity with tools like Great Expectations, Pandas, Plotly, or MS Power Automate is a plus. Able to work collaboratively and independently in a fast-paced environment. Ready to Apply? If you're excited by the opportunity to More ❯

Technical & Analytical Skills Hands-on experience with large data sets and data profiling. Proficiency in data tools: Power BI, Excel, SQL, Python, Databricks. Familiarity with tools like Great Expectations, Pandas, Plotly, or MS Power Automate is a plus. Able to work collaboratively and independently in a fast-paced environment. Ready to Apply? If you're excited by the opportunity to More ❯

Master’s in Bioinformatics, Computer Science, Data Engineering, or related field. 4+ years of experience in data engineering or bioinformatics data management. Strong Python and SQL skills; experience with Pandas, PySpark, Dask, or similar frameworks. Familiar with Linux, Docker, and modern data architectures (relational, object, non-relational). Experience with orchestration tools (Airflow/Prefect) and cloud platforms (AWS preferred More ❯

Master’s in Bioinformatics, Computer Science, Data Engineering, or related field. 4+ years of experience in data engineering or bioinformatics data management. Strong Python and SQL skills; experience with Pandas, PySpark, Dask, or similar frameworks. Familiar with Linux, Docker, and modern data architectures (relational, object, non-relational). Experience with orchestration tools (Airflow/Prefect) and cloud platforms (AWS preferred More ❯

computer science, or a proven record of delivering quality software Curious, proactive, and motivated to write great code and improve as a developer Bonus Points For Experience With NumPy, Pandas HTML, CSS, JavaScript Git LaTeX Cybersecurity best practices Financial, legal, or compliance-related tech Location & Setup The engineering team is fully remote, with the existing developers based in South Africa. More ❯

trading constraints. Automate Data Pipelines, designing and managing workflows for collecting, cleaning, and storing large volumes of financial data (e.g., price, volume, fundamentals, alternative data), often using tools like Pandas, NumPy, and Dask. Collaborate Across Teams for Deployment, working with researchers, traders, and DevOps teams to integrate Python models into production environments (e.g., through APIs, microservices, or containerized systems like More ❯

experiments into production-ready systems What You’ll Bring 6+ years of software engineering experience 4+ years building and deploying ML/AI models in production Proficiency in Python (pandas, scikit-learn, PyTorch, etc.) Experience with modern backend stacks (TypeScript, Node.js, Go, or similar) Strong understanding of ML principles and model evaluation Experience with cloud-based model deployment (GCP preferred More ❯

experiments into production-ready systems What You’ll Bring 6+ years of software engineering experience 4+ years building and deploying ML/AI models in production Proficiency in Python (pandas, scikit-learn, PyTorch, etc.) Experience with modern backend stacks (TypeScript, Node.js, Go, or similar) Strong understanding of ML principles and model evaluation Experience with cloud-based model deployment (GCP preferred More ❯

s degree in Data Science, Computer Science, AI, or related field preferred • Equivalent hands-on experience in applied analytics or data-driven product work also considered • Strong Python skills (pandas, NumPy, seaborn, matplotlib); working knowledge of SQL • Comfortable working with production data, debugging with metrics, and making actionable recommendations • Experience with agile development and cross-functional collaboration • Familiarity with LangGraph More ❯

/ML senior engineering roles focused on Natural Language Processing use cases. Programming: Expert in Python with experience in libraries/frameworks such as PyTorch, TensorFlow, scikit-learn, Keras, Pandas, and NumPy. Data: Experienced in using SQL and working with databases. Education: A degree in Computer Science with specialization in AI or Machine Learning, or equivalent combination of education and More ❯

the latest developments in AI, machine learning, and data science methodologies. Experienced Needed: Masters or PhD in a STEM subject Proficiency in Python, with experience in libraries such as pandas, scikit-learn, TensorFlow, or PyTorch. Solid SQL skills and experience working with relational databases. Exposure to cloud platforms (AWS, GCP, or Azure) would be advantageous. Strong analytical and problem-solving More ❯

the latest developments in AI, machine learning, and data science methodologies. Experienced Needed: Masters or PhD in a STEM subject Proficiency in Python, with experience in libraries such as pandas, scikit-learn, TensorFlow, or PyTorch. Solid SQL skills and experience working with relational databases. Exposure to cloud platforms (AWS, GCP, or Azure) would be advantageous. Strong analytical and problem-solving More ❯

a 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 More ❯

a 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 More ❯

driven 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 More ❯

technical 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 More ❯

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 pipelines More ❯

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 pipelines More ❯

For Proven 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 More ❯

expertise 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 More ❯

especially LLMs and CNNs) and frameworks (e.g., TensorFlow, PyTorch). Experience with programming languages such as Python, C++, and CUDA. Familiarity with data processing and analysis tools (e.g., NumPy, Pandas). Knowledge of hardware architectures and performance optimization is a plus. Strong analytical and problem-solving skills, with attention to detail. Excellent communication skills and ability to work collaboratively in More ❯

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/CD More ❯

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/CD More ❯