1 to 25 of 27 Part-Time Statistics Jobs in the UK

Formal training or certification on software engineering concepts and 5+ years applied experience \n MS or PhD in Computer Science, Data Science, Statistics, Mathematical Sciences, or Machine Learning; strong background in mathematics and statistics. \n Extensive expertise applying data science and ML to business problems with strong programming in Python ...

skills: \n \n Advanced degree (Master's or PhD) in a STEM subject (including Data Science, Computer Science, Engineering, Physical Sciences, Applied Mathematics or Statistics) \n Extensive practical research experience and a proven track record of applying AI and adjacent techniques to solve real-world problems in industry or academia ...

Master Data Management, Data Lineage analysis, Metadata Management, Data Quality assessment and management, Data Transformation and migration \n Ability to apply advanced analytics and statistics to business problems \n Proven experience of working with large volumes of data, applying tools such as SAS, R, Python, SQL, PowerBI, Tableau, Looker ...

contributing to the team’s engineering standards and practices. \n\n Essential Qualifications: \n \n Masters degree (or equivalent) in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a quantitative field such as Economics. \n Professional experience in a data science, ML engineering, or applied data role. \n Strong Python ...

contributing to the team’s engineering standards and practices. \n\n Essential Qualifications: \n \n Masters degree (or equivalent) in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a quantitative field such as Economics. \n Professional experience in a data science, ML engineering, or applied data role. \n Strong Python ...

nYou will contribute defining impactful OKRs to work throughout the half of the year.\n \n\n Qualifications \n \n \nBachelor’s degree in Statistics, Economics, or other relevant fields. \n \n \n2+ years of experience in a marketing analytics or data analytics role.\n \n \nAdvanced SQL skills, Python ...

Advanced SQL querying skills. \n Competent data analysis in Python. \n Experience in taking open ended business questions, then use big data and statistics to create analysis that can provide an answer to the questions at hand. \n Experience with customer analytics such as user behavioral analysis, campaign analysis, etc. ...

science, mathematics, physics, engineering or related STEM field \n Strong problem-solving skills and solid grounding in classical ML and deep learning: from applied statistics and traditional machine learning algorithms to transformers and SOTA deep learning \n Excellent collaboration and communication skills, both with teams and in client-facing engagements ...

solve challenging problems together. \n MINIMUM (ESSENTIAL) REQUIREMENTS: \n \n \nA minimum of a 2.1 degree in Computer Science, AI, Data Science, Statistics or in a similar quantitative field. \n \n\n \n \nDemonstrable experience of deploying modern AI/ML solutions into production, including prompt engineering, retrieval-augmented generation ...

spend.\n \n \nAct as a subject matter expert on our whole measurement framework.\n \n\n Qualifications \n \n \nBachelor’s degree in Statistics, Economics, or other relevant fields. \n \n \n4+ years of experience in a marketing analytics or data science role. \n \n \nLeadership/management experience ...

solve challenging problems together. \n MINIMUM (ESSENTIAL) REQUIREMENTS: \n \n \nA minimum of a 2.1 degree in Computer Science, AI, Data Science, Statistics or in a similar quantitative field. \n \n\n \n \nDemonstrable experience of deploying modern AI/ML solutions into production, including prompt engineering, retrieval-augmented generation ...

solve challenging problems together. \n MINIMUM (ESSENTIAL) REQUIREMENTS: \n \n \nA minimum of a 2.1 degree in Computer Science, AI, Data Science, Statistics or in a similar quantitative field. \n \n\n \n \nProven experience of leading multi-disciplinary teams to deliver AI/ML solutions to production. ...

nData visualisation (Looker)\n \n \nSQL (our stack is based around BigQuery)\n \n \nCoding (Python, Github)\n \n\n\n \nKnowledge of statistics and experiment design.\n \n\n The interview journey: \n \n \nTA screening - 30 mins\n \n \n 1st stage with Head of Pricing & Revenue Management ...

Required Qualifications, Capabilities, and Skills: \n \n Experience in machine learning engineering roles \n Degree in a quantitative discipline (Computer Science, Mathematics, Statistics) \n Proven ability to develop and deploy business-critical, data-intensive applications \n Extensive experience with AWS and Kubernetes \n Proficiency with lower-level libraries such ...

financial services industry, including the products, data, typical ML applications, and related regulations\n \n \nExcellent technical skills in Python, SQL, and statistics\n \n \nHands-on experience across the model lifecycle from scoping and model development to deployment and monitoring\n \n\n Nice to have \n \n \nExperience ...

financial services industry, including the products, data, typical ML applications, and related regulations\n \n \nExcellent technical skills in Python, SQL, and statistics\n \n \nHands-on experience across the model lifecycle from scoping and model development to deployment and monitoring\n \n\n Nice to have \n \n \nExperience ...

modeling recommendations. \n\n What You'll Bring to the Table\n \n A Master's degree or PhD in Data Science, Computer Science, Statistics, or a related quantitative field. \n Proven, extensive experience in leadership and people management, with a demonstrated ability to mentor, guide, and develop Data Scientists. ...

Experience with neural network architectures for generative or predictive applications \n Familiarity with game development engines or creative automation tools \n Background in mathematics, statistics, or computational science \n\n What’s on offer \n \n £/€1,000 learning fund \n Twice-yearly bonus (with part of it guaranteed ...

effective communication both internally and externally\n \n \nExperience working in a highly regulated industry\n \n \nStrong technical skills in Python, SQL, and statistics\n \n \nExperience across the model lifecycle from scoping and model development to deployment and monitoring\n \n\n \n Nice to have ...

concise documentation and analysis.\n \n\n NICE TO HAVE BUT NOT ESSENTIAL \n \n \nProficient in python’s various data transformation, visualisation and statistics libraries i.e. pandas, numpy , scipy and plotly\n \n \nExperience leading a team or owning a whole product domain\n \n\n PROCESS ...

pair programming or mob programming. \n Working with data scientists to productionise advanced data deliverables, such as machine learning models \n Working knowledge of statistics \n Working with multidisciplinary digital and technology teams \n Working within the public sector \n Working with data scientists to productionise advanced data deliverables, such ...

pair programming or mob programming. \n Working with data scientists to productionise advanced data deliverables, such as machine learning models \n Working knowledge of statistics \n Working with multidisciplinary digital and technology teams \n Working within the public sector \n\n \n Job Benefits \n Support in applying ...

platforms such as Optimizely and Leanplum \n• Experience of manipulating, analysing and synthesising data using different sources \n• Good knowledge of experimental design and statistics for testing \n• Strong communication and presentation skills \n• Managing and influencing cross functional stakeholders \n• University degree of 2:1 or higher ...

data scientists to productionise advanced data deliverables, such as machine learning models \n Infrastructure-as-Code (e.g. Terraform, Cloud Formation) \n Working knowledge of statistics \n Working with multidisciplinary digital and technology teams \n Working within the public sector \n\n At this point, we hope you're feeling excited ...

candidate's experience. \n\n Required qualifications, capabilities, and skills \n \n Masters or PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Statistics \n Solid understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders etc.) \n Specialism or well-researched ...