uncertainty quantification, model evaluation, and statistical inference is highly valued. Python expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage More ❯
uncertainty quantification, model evaluation, and statistical inference is highly valued. Python expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage More ❯
Bradford, England, United Kingdom Hybrid/Remote Options
Tata Consultancy Services
Balancing. • CI/CD & DevOps Integration. • AWS (ECS, fargate , EC2, SNS, SQS, Cloudwatch, EKS, Kubernetes). Desirable skills/knowledge/experience: • Familiarity with data analysis libraries like Pandas, NumPy, and Scikit-learn. • Knowledge of data science and machine learning concepts and tools. Good to have: • Strategic thinking and problem-solving. • Collaboration and teamwork. • Effective communication and stakeholder management. • Adaptability More ❯
Data Scientist, Machine Learning Engineer, ML Engineer, Data Science Engineer, High-Performance Engineering, Python, Data, Pandas, numpy, scikit-learn, pytorch - Oxford - up to 55K About the Role: Join an elite engineering organisation's Software Engineering & Data team, where you'll develop cutting-edge machine learning solutions that directly impact performance at the highest level of competition click apply for full More ❯
into technical solutions. Optimize models for scalability, performance, and accuracy. Mentor junior engineers and review code for quality and best practices. Required Skills & Experience Strong proficiency in Python (Pandas, NumPy, Scikit-learn, FastAPI/Flask). Experience with machine learning workflows: data preprocessing, model training, evaluation, and deployment preferably using Microsoft stack - Azure ML, Azure Data Factory, Synapse Analytics, and More ❯
managing cloud-based solutions. Experience with Cloud services such as Azure Data Services, ADLS and AKS. Experience with Python and PySpark for distributed data processing, along with proficiency in Numpy, Pandas and other data manipulation libraries. Experience in optimizing big data architectures for high availability and performance. Strong problem-solving skills, analytical mindset, and ability to work in fast-paced More ❯
experience in Data Operations, Data Engineering, or similar, within a Trading/Investment firm, or a firm providing services to Trading or Investment firms (Essential) Excellent Python skills (Pandas, NumPy), SQL Excellent ETL experience managing the full end-to-end process from Data Ingestion through to Data Publishing and maintenance of data pipelines If you feel your experience is a More ❯
experience in Data Operations, Data Engineering, or similar, within a Trading/Investment firm, or a firm providing services to Trading or Investment firms (Essential) Excellent Python skills (Pandas, NumPy), SQL Excellent ETL experience managing the full end-to-end process from Data Ingestion through to Data Publishing and maintenance of data pipelines If you feel your experience is a More ❯
complex datasets. Desirable Experience & Skills Practical knowledge of data engineering practices (designing and building robust data pipelines) Knowledge of python and core libraries applicable to data science (e.g., pandas, numpy, statsmodel More ❯
this world leading Energy Trading company. The role would be part of a long term Strategic IT project, with ongoing contract extensions. Core Technical Skills Programming: Python Data Handling: NumPy, Pandas, SQL Version Control: Git/GitHub System Integration & Deployment Model Deployment: Flask, FastAPI, MLflow Model Serving: Triton Inference Server, Hugging Face Inference Endpoints API Integration: OpenAI, Anthropic, Cohere, Mistral More ❯
this world leading Energy Trading company. The role would be part of a long term Strategic IT project, with ongoing contract extensions. Core Technical Skills Programming: Python Data Handling: NumPy, Pandas, SQL Version Control: Git/GitHub System Integration & Deployment Model Deployment: Flask, FastAPI, MLflow Model Serving: Triton Inference Server, Hugging Face Inference Endpoints API Integration: OpenAI, Anthropic, Cohere, Mistral More ❯
complex datasets. Desirable Experience & Skills: Practical knowledge of data engineering practices (designing and building robust data pipelines) Knowledge of Python and core libraries applicable to data science (eg, pandas, numpy, statsmodels) Hybrid - 3 days from the client's office. More ❯
complex datasets. Desirable Experience & Skills Practical knowledge of data engineering practices (designing and building robust data pipelines) Knowledge of python and core libraries applicable to data science (e.g., pandas, numpy, statsmodel More ❯
them with reliable datasets and dashboards. Key Skills & Experience (Must-Have) Strong hands-on experience with Python programming (functions, classes, OOP, error handling). Practical experience with Pandas and NumPy for data processing. Good understanding of SQL and working with relational databases. Experience using Git for version control. Basic understanding of writing unit tests and maintaining code quality. Good to More ❯
them with reliable datasets and dashboards. Key Skills & Experience (Must-Have) Strong hands-on experience with Python programming (functions, classes, OOP, error handling). Practical experience with Pandas and NumPy for data processing. Good understanding of SQL and working with relational databases. Experience using Git for version control. Basic understanding of writing unit tests and maintaining code quality. Good to More ❯
secure, deployable AI solutions Key Skills & Experience Required Senior-level experience in data science or a quantitative field Proficient programming skills (Python preferred); familiarity with core data science libraries (NumPy, Pandas, Scikit-Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science methods (e.g. ML, NLP More ❯
deliver measurable business outcomes. What You’ll Bring 🔥Deep knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). ⚙️Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning frameworks (PyTorch, TensorFlow). 🚀Strong leadership in project delivery, architecture, and technical decision-making. 💡Excellent communicator, able to simplify complex ideas for any audience. More ❯
deliver measurable business outcomes. What You’ll Bring 🔥Deep knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). ⚙️Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning frameworks (PyTorch, TensorFlow). 🚀Strong leadership in project delivery, architecture, and technical decision-making. 💡Excellent communicator, able to simplify complex ideas for any audience. More ❯
mentoring, and peer reviews. Continuously evolve the distributed software stack, improving performance and reliability across platforms. What Youll Bring Strong proficiency in Python , including modern data engineering libraries (Pandas, NumPy, Dask, Polars, PySpark). Experience designing or maintaining distributed systems or microservice architectures . Background as a software engineer or data engineer experience in energy markets is a significant advantage More ❯
and peer reviews. Continuously evolve the distributed software stack, improving performance and reliability across platforms. What You’ll Bring Strong proficiency in Python , including modern data engineering libraries (Pandas, NumPy, Dask, Polars, PySpark). Experience designing or maintaining distributed systems or microservice architectures . Background as a software engineer or data engineer — experience in energy markets is a significant advantage More ❯
deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science – scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large “Big Data” environments. Command knowledge in Python and API Development Excellent grasp of software Engineering practices – Object Orientated More ❯
deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science – scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large “Big Data” environments. Command knowledge in Python and API Development Excellent grasp of software Engineering practices – Object Orientated More ❯
outputs. Stay informed on emerging trends, technologies, and best practices in data science. Experience Required: Proven experience as a Data Scientist with proficiency in Python and libraries such as NumPy, Pandas, Scikit-learn, Matplotlib, and Plotly. Strong background in statistical modelling, machine learning, and data mining, with experience working on time-series data. Knowledge of data engineering principles, including pipelines More ❯
