live production environment. Experience and strong proficiency in programming languages for data science, e.g., SQL, R and Python alongside the ability to use tools and packages such as Alteryx, Jupyter notebook, R Markdown, TensorFlow, Keras, Pytorch etc. Practical expertise in producing reproducible code and pipelines including documentation, governance and assurance frameworks, automation and code review using tools such as Git. More ❯
and interpreting large datasets. Ability to apply statistical techniques to validate models and algorithms. Data Manipulation & Analysis: Proficient in data manipulation and analysis using tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau to communicate insights effectively. Our offer: Cash: Depends on experience Equity: Generous equity package, on a standard vesting More ❯
a related field. Proven experience in machine learning applications such as recommendation systems, segmentation, and marketing optimisation. Proficiency in Python, SQL, Bash, and Git, with hands-on experience in Jupyter notebooks, Pandas, and PyTorch. Familiarity with cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong problem-solving skills and a passion for driving measurable business impact. Knowledge More ❯
a related field. Proven experience in machine learning applications such as recommendation systems, segmentation, and marketing optimisation. Proficiency in Python, SQL, Bash, and Git, with hands-on experience in Jupyter notebooks, Pandas, and PyTorch. Familiarity with cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong problem-solving skills and a passion for driving measurable business impact. Knowledge More ❯
learning models Build AI systems using Large Language Models Build processes for extracting, cleaning and transforming data (SQL/Python) Ad-hoc data mining for insights using Python + Jupyter notebooks Present insights and predictions in live dashboards using Tableau/PowerBI Lead the presentation of findings to clients through written documentation, calls, and presentations Actively seek out new opportunities More ❯
improve our ability to serve clients. Tech Skills Required: Advanced level of coding in Python for Data Science Software engineering architecture design for application with integrated Data Science solutions Jupyter server/notebooks AWS: EC2, Sagemaker, S3 Git version control SQL skills include selecting, filtering, aggregating, and joining data using core clauses, use of CTEs, window functions, subqueries, and data More ❯
learning models Build AI systems using Large Language Models Build processes for extracting, cleaning and transforming data (SQL/Python) Ad-hoc data mining for insights using Python + Jupyter notebooks Present insights and predictions in live dashboards using Tableau/PowerBI Lead the presentation of findings to clients through written documentation, calls and presentations Actively seek out new opportunities More ❯
design and deployment. Strong software engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). Experience with cloud services (e.g., AWS, GCP, Azure) for More ❯
storage and retrieval. Strong software engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). Experience with cloud services (e.g., AWS, GCP, Azure) for More ❯
a related field. 🧠 Solid understanding of data analysis, machine learning concepts, and statistical methods. 🐍 Proficiency in Python (e.g., Pandas, Scikit-learn, NumPy) or R, with exposure to tools like Jupyter, SQL, or cloud platforms (e.g., AWS, GCP). 📊 Experience working with data—through academic projects, internships, or personal work—and a curiosity to learn more. 🗣️ Strong communication skills to share More ❯
a related field. 🧠 Solid understanding of data analysis, machine learning concepts, and statistical methods. 🐍 Proficiency in Python (e.g., Pandas, Scikit-learn, NumPy) or R, with exposure to tools like Jupyter, SQL, or cloud platforms (e.g., AWS, GCP). 📊 Experience working with data—through academic projects, internships, or personal work—and a curiosity to learn more. 🗣️ Strong communication skills to share More ❯
field. Proven experience in machine learning applications such as recommendations, segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science teams. Deep knowledge More ❯
field. Proven experience in machine learning applications such as recommendations, segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science teams. Deep knowledge More ❯
field. Proven experience in machine learning applications such as recommendations, segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science teams. Deep knowledge More ❯
AI/ML/Data Science apprenticeship programme. Core Skills & Competencies Technical Skills Programming proficiency in Python and common ML libraries such as TensorFlow, PyTorch, or similar. Experience with Jupyter Notebooks and version control (Git/GitHub). Basic understanding of supervised/unsupervised learning, neural networks, or clustering. Analytical Abilities Ability to interpret data trends, visualize outputs, and debug More ❯
Learning, AI, Statistics, Economics or equivalent) 5+ years of professional working experience Someone who thrives in the incremental delivery of high quality production systems Proficiency in Java, Python, SQL, Jupyter Notebook Experience with Machine Learning and statistical inference. Understanding of ETL processes and data pipelines and ability to work closely with Machine Learning Engineers for product implementation Ability to communicate More ❯
Playwright or similar testing frameworks. REST APIs: Strong understanding of integrating and working with RESTful services. Data Skills: Experience in data wrangling/analysis (e.g., using SQL or Python, Jupyter Notebook). Collaboration: Experience working in an Agile environment (Scrum/Kanban). Problem-Solving: Strong analytical and troubleshooting skills. Desirable Skills Familiarity with state management libraries (MobX, Redux). More ❯
clustering, classification, predictive modelling) through coursework, internships, or independent projects You are proficient in Python (especially pandas, numpy, scikit-learn, or similar libraries) and comfortable performing data analysis using Jupyter notebooks or similar tools You are comfortable writing clear, efficient SQL for extracting, cleaning, and preparing datasets, demonstrated through coursework, internships, or personal analytical projects You have demonstrated initiative by More ❯
and other Qualtrics products Acquire data from customers (usually sftp or cloud storage APIs) Validate data with exceptional detail orientation (including audio data) Perform data transformations (using Python and Jupyter Notebooks) Load the data via APIs or pre-built Discover connectors Advise our Sales Engineers and customers as needed on the data, integrations, architecture, best practices, etc. Build new AWS More ❯
Defender XDR, Entra, Purview). Create scripts, APIs, and orchestrations that reduce manual effort and improve speed and accuracy in security operations. - Tell Stories with Data: Use tools like Jupyter Notebooks, Kusto Query Language (KQL), and Python to query and visualize large-scale security datasets. Translate telemetry into insights and share narratives that influence decision-making across engineering and leadership … engineering, preferably in cloud-native or regulated environments. - Strong programming/scripting skills (Python preferred) with a focus on infrastructure and operations tooling. - Experience working with large datasets in Jupyter Notebooks and building dashboards or reports for security posture and compliance. - Strong communication skills with an ability to convey technical concepts to non-technical stakeholders. - Role is UK based and More ❯
in a transparent environment, engaging with the whole investment process Preferred Technical Skills Expert in Python and/or KDB/Q Proficient in modern data science tools stacks (Jupyter, pandas, numpy, sklearn) with machine learning experience Good understanding of using Slurm or similar parallel computing tools Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related More ❯
design and implement data engineering and AI/ML infrastructure. Things we're looking for: Proficiency in data analysis, insights generation and using cloud-hosted tools (e.g., BigQuery, Metabase, Jupyter). Strong Python and SQL skills, with experience in data abstractions, pipeline management and integrating machine learning solutions. Adaptability to evolving priorities and a proactive approach to solving impactful problems More ❯
the role. Strong verbal and written communication skills, with a track record of collaborating across both technical and non-technical teams. Practical knowledge of PowerBI is advantageous; familiarity with Jupyter Notebooks is helpful but not essential. A personal or professional interest in markets and trading (e.g., independent trading projects) is viewed positively. More ❯
the role. Strong verbal and written communication skills, with a track record of collaborating across both technical and non-technical teams. Practical knowledge of PowerBI is advantageous; familiarity with Jupyter Notebooks is helpful but not essential. A personal or professional interest in markets and trading (e.g., independent trading projects) is viewed positively. More ❯
