a Data Scientist Strong proficiency in programming languages such as Python or R for data analysis, with experience in libraries like pandas, NumPy, scikit-learn, and TensorFlow/PyTorch. Solid understanding of statistical analysis and experience in applying techniques like regression, hypothesis testing, and multivariate analysis. Hands-on More ❯
understanding of statistical analysis and modeling techniques, including linear regression, time series, decision trees, and clustering algorithms. Proficient in machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch, Keras) for building and deploying predictive models. Proficient in Python, R, or similar programming languages for data analysis and machine learning. More ❯
understanding of statistical analysis and modeling techniques, including linear regression, time series, decision trees, and clustering algorithms. Proficient in machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch, Keras) for building and deploying predictive models. Proficient in Python, R, or similar programming languages for data analysis and machine learning. More ❯
in Python (preferred) or R, with experience in SQL for data manipulation and analysis. Strong understanding of machine learning algorithms and frameworks like scikit-learn, TensorFlow, or PyTorch. Experience with cloud platforms (AWS, GCP, or Azure) for model deployment and data processing. Proficiency in data visualisation tools such More ❯
field. 3+ years of experience delivering AI/ML solutions in production environments. Proficient in Python and key data science libraries (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Hands-on expertise with LLMs and agentic workflows (fine-tuning, prompt engineering, retrieval-augmented generation). Strong grasp of the More ❯
Skills Programming Languages: Strong proficiency in Python, R, and SQL. Familiarity with Spark. Data Manipulation & Analysis: Experience with libraries like Pandas, NumPy, and Scikit-learn for data cleaning, manipulation, and model building. Machine Learning & Statistical Modeling: Solid understanding of supervised and unsupervised learning, feature engineering, model selection, and More ❯
techniques, including LLMs, GenAI, and automated AI systems. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and data science libraries (e.g., NumPy, pandas, scikit-learn). Proficiency in Python, R, or other relevant programming languages. Proficiency in working with large datasets, data wrangling, and data preprocessing. Experience in More ❯
degree in a STEM (Science, Technology, Engineering, or Mathematics) discipline. Strong programming skills in Python, including experience with libraries such as Pandas, NumPy, Scikit-learn, and TensorFlow/PyTorch. Experience with data processing, analysis, and visualization. Knowledge of machine learning techniques and statistical analysis. Familiarity with cloud computing More ❯
Barnsley, South Yorkshire, UK Hybrid / WFH Options
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degree in a STEM (Science, Technology, Engineering, or Mathematics) discipline. Strong programming skills in Python, including experience with libraries such as Pandas, NumPy, Scikit-learn, and TensorFlow/PyTorch. Experience with data processing, analysis, and visualization. Knowledge of machine learning techniques and statistical analysis. Familiarity with cloud computing More ❯
machine learning and AI development Strong foundation in machine learning algorithms and statistical modeling Expert-level proficiency in Python and related ML libraries (scikit-learn, TensorFlow, PyTorch) Experience with deep learning frameworks and architectures (CNNs, RNNs, Transformers) Practical experience with MLOps tools and practices Strong knowledge of data More ❯
in industry Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or related quantitative field Strong programming skills in Python ecosystem (numpy, pandas, scikit-learn) Proficient in SQL for complex data manipulation and analysis Solid understanding of machine learning algorithms (both supervised and unsupervised) Experience with cloud platforms More ❯
technical and non-technical stakeholders through effective data visualisation and building of reporting frameworks Comfortable with Python data science libraries such as pandas, scikit-learn, numpy, statsmodels Strong SQL experience including analytic functions, performance tuning, data wrangling Ability to work collaboratively and proactively in a fast-paced environment More ❯
or a related field. • Strong understanding of Python, R, SQL, or other programming languages used in data science. • Experience with pandas, NumPy, Matplotlib, Scikit-Learn, TensorFlow, or PyTorch . • Knowledge of machine learning algorithms, data mining, and predictive analytics . • Familiarity with big data technologies and cloud platforms More ❯
managing and mentoring teams. Technical Skills: Proficiency in programming languages such as Python, R, or similar. Experience with machine learning frameworks (e.g., TensorFlow, Scikit-learn). Strong knowledge of SQL and database management. Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure). More ❯
to aviation industry problems Strong programming skills in Python, R, or similar languages for data analysis Experience with machine learning libraries and frameworks (scikit-learn, TensorFlow, PyTorch) Proficiency in SQL and experience working with large, complex datasets Knowledge of statistical analysis, experiment design, and modeling techniques Understanding of More ❯
experience demonstrating relevant skills, preferably with some exposure to the sports sector. Technical Skills: Proficiency in Python (especially the PyData stack: pandas, numpy, scikit-learn, XGBoost), and experience with Git for version control is essential. Strong understanding of machine learning algorithms including linear/logistic regression, decision trees More ❯
Hadoop, Kafka, or similar. Timeseries Database: InfluxDB or TimescaleDB, or similar. Cloud Platforms: AWS Redshift, Azure Synapse, or similar. ML/AI Tools: scikit-learn, TensorFlow, PyTorch. Data Visualization: Power BI, Tableau, or similar. Version Control: Git. Preferred Qualifications: Experience with energy management systems or SCADA. Knowledge of More ❯
br Exposure to LLMs from model families such as Anthropic, Meta, Amazon, and OpenAI. br Familiarity with tools and packages like Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks. br Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache Airflow. br Proficiency in data pre More ❯
Advanced Python programming skills, with a strong emphasis on writing efficient, scalable, and maintainable code. Proven experience with TensorFlow/PyTorch/Jax, Scikit-learn, and MLOps workflows for training, deployment, and monitoring of ML models. Experience working with Polars and/or Pandas for high-performance data More ❯
and PyTorch. Exposure to LLMs from model families such as Anthropic, Meta, Amazon, and OpenAI. Familiarity with tools and packages like Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks. Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache Airflow. Proficiency in data pre-processing, data More ❯
to become a fluent Python programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid More ❯
that demonstrates some of the qualities we’re looking for. Technical Skills: Strong proficiency in Python and relevant frameworks/libraries (NumPy, Pandas, Scikit-Learn, TensorFlow/PyTorch, LangChain, LangGraph, Hugging Face, etc.). Experience working with LLMs and AI models in production environments. Experience building RAG-based More ❯
techniques, with hands-on experience in either academia or industry. Proficiency in Python and experience with ML/NLP libraries like TensorFlow, PyTorch, scikit-learn, or Hugging Face. Experience working with cloud platforms such as AWS, GCP, or Azure. Familiarity with advanced NLP methods, including Prompt Engineering, Parameter More ❯
techniques, with hands-on experience in either academia or industry. Proficiency in Python and experience with ML/NLP libraries like TensorFlow, PyTorch, scikit-learn, or Hugging Face. Experience working with cloud platforms such as AWS, GCP, or Azure. Familiarity with advanced NLP methods, including Prompt Engineering, Parameter More ❯
domains (e.g. Natural Language Processing, Computer Vision) and expert knowledge in statistics. You are proficient in the Python Machine Learning stack (NumPy, pandas, scikit-learn, TensorFlow/PyTorch), have extensive experience in software development and are skilled with various database systems (relational/NoSQL). You are experienced More ❯
