51 to 75 of 128 Permanent Bayesian Methods Jobs

supervised ML algorithms, tuning, and performance evaluation. Experience with a range of feature engineering techniques (e.g. target encoding).Solid grasp of frequentist and Bayesian statistics for parameter estimation and experimentation. Experience in writing clean, production-grade Python code for both model training and inference. Excited to leverage ...

with a proven record of success in online data science competitions, such as Kaggle. Experience in deep learning, reinforcement learning, non‐convex optimisation, Bayesian non‐parametrics, NLP or approximate inference. Excellent reasoning skills and mathematical ability. Strong programming skills and experience working with Python, Scikit‐Learn, SciPy ...

data pipelines using dbt, Airflow, and Snowflake. Beyond querying, you use Python for advanced automation and forecasting, and you apply statistical rigor (e.g., Bayesian statistics, causal inference) to solve complex product problems.Commercial & Risk Mindset: You possess deep commercial fluency, understanding the unit economics of a fintech product ...

data pipelines using dbt, Airflow, and Snowflake. Beyond querying, you use Python for advanced automation and forecasting, and you apply statistical rigor (e.g., Bayesian statistics, causal inference) to solve complex product problems. Commercial & Risk Mindset: You possess deep commercial fluency, understanding the unit economics of a fintech ...

rich environments Strong statistical knowledge Experience with product analytics and behavioural tracking Experience mentoring or coaching other analysts Nice to have Knowledge of Bayesian or Frequentist experimentation approaches Experience with event-level analytics platforms Predictive analytics exposure The team You'll report into the Analytics Team Lead ...

Make your mark for patientsWe are looking for a Principal Computational Methodologist who is curious, collaborative, and impact-driven to join our Advanced Methods and Data Science team within Biometrics and Data Science, based in any of our Brussels (Belgium), Slough (UK) or Raleigh (US).About the roleYou will … help shape how advanced AI, machine learning, and computational methods support clinical development. You will design, validate, and deploy models that help teams make evidence-based decisions in areas such as biomarker discovery, clinical trial design, operational efficiency, and patient experience. You will guide scientific thinking, turn complex methods ...

Stats or Engineering degree.Outstanding background in probability and statisticsExperience and interest in modern machine learning techniques, for example, deep learning, Bayesian methods and graphical modelsProgramming experience with python, julia or RYou will be joining a progressive and exciting company committed to excellence. They offer an excellent ...

teams to inform regulatory strategy and HEOR decisions. The role requires strong statistics background, proficiency in SAS, R and Python, and experience with Bayesian or probabilistic ML methods. You will advance analytical workflows in scalable environments. #J-18808-Ljbffr ...

fintech and Cleo's mission to make money easier and more human Nice to have: causal inference depth (CUPED, Bayesian methods, PSM, uplift modelling) and the judgement to know when it's worth the effort Nice to have: genuine enthusiasm for agentic AI as a force ...

products PhD or other experience in a research environment Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background Benefits Competitive salary and equity in a fast‐growing start‐up We serve lunch every weekday ...

initiative and are deeply accountable to your internal customers and engineering colleagues. Bonus: experience with implementing solutions for adaptive experimentation ML (contextual bandits, Bayesian optimization or RL-based allocation) Additional Information Bring all of you to work We create the conditions for high performers to thrive, through ...

replacement for clinical and statistical expertise, but as a powerful complement to it. We hold ourselves to measurable standards of improvement, and we build methods that can be evaluated, reproduced, and trusted in regulatory settings. You will work across the enterprise to define and deliver on AstraZeneca's most … questions — leading cross-functional teamsspanning the keyBioPharmaceuticalsdisease areas of cardiovascular, renal, metabolic disease, respiratory,immunologyand cell-therapy. You and the team will develop reusable methods and enterprise-scale approaches that measurably advance the late-stage drug pipeline. This is a high-visibility opportunity to shape how AstraZeneca does ...

teams to design and implement new statistical and machine learning features across Optimizely’s product suite. Conduct rigorous testing and validation of new statistical methods and ensure seamless integration into the platform. Analyze product performance data to optimize existing features and provide actionable recommendations for improvement. Leverage AI agents … deploy new statistical capabilities. Research and Innovation Partner with academic and industry researchers to explore cutting-edge statistical methods and machine learning innovations. Identify emerging trends in experimentation and statistics that could enhance Optimizely’s offerings. Propose and prototype advanced statistical techniques to solve challenging business problems faced ...

your strong analytical and problem-solving skills, you will work with complex real-world datasets from field deployments and apply a combination of Bayesian inference, machine learning , and data-driven modelling techniques to deliver robust, interpretable results. We are looking for a hands-on, experienced data scientist … processing, anomaly detection, ML classification) Gas modelling for source localisation and quantification Total site quantification of emissions Research and apply machine learning and AI methods to complement physics-based models, improve detection sensitivity, and automate performance assessment Take a key role in advancing Mirico’s gas-modelling capability , driving ...

sitting at the intersection of modern machine learning and quantum computing — with two complementary directions. ML for quantum — using neural networks and learning-based methods to accelerate quantum computation (e.g. circuit optimisation and compilation, error mitigation, calibration, variational-parameter optimisation, and surrogate modelling of quantum processes). …/with quantum — building and adapting classical AI methods, including neural networks and large language models, so they can benefit from quantum hardware and algorithms. You don't need to be a world expert in either quantum or LLMs — but you should be genuinely comfortable with neural networks and ...

producing strong quantitative evidence to inform strategy and improve outcomes for people and communities. You will develop predictive models, apply Bayesian methods, and analyse time-series data using Python or R and SQL, translating complex findings for non-technical colleagues in a hybrid, 4-days ...

research with mentoring PhD students and collaboration with clinicians, computer scientists and mathematicians. Proficiency in Python, Julia, R and MATLAB, plus experience with Bayesian inference and HPC #J-18808-Ljbffr ...

data, and user feedback to identify high-impact opportunities. Execute and monitor A/B and multi-variant tests to ensure rigorous methodology (Bayesian, Multi-Armed Bandits, etc.), consistent data flow, and clear understanding of success metrics. Report on A/B testing performance (velocity, lift, statistical ...

data, and user feedback to identify high-impact opportunities. Execute and monitor A/B and multi-variant tests to ensure rigorous methodology (Bayesian, Multi-Armed Bandits, etc.), consistent data flow, and clear understanding of success metrics. Report on A/B testing performance (velocity, lift, statistical ...

firms and telecoms; including Nissan, L'Oréal, Carrefour, WHSmith, Orange, Beiersdorf, BNP Paribas, and Samsung. Our success stems from combining advanced data technologies, agile methods for quick delivery, and dedicated teams of data scientists, data engineers, business consultants, and data analysts. Our 1,800 employees operate in 25 countries … client stakeholders. Advanced Modelling: Proven ability to implement a range of complex models such as time-series forecasting, gradient boosting, clustering, NLP, and Bayesian inference. ML-Ops & Orchestration: Strong experience with MLOps tools for orchestration, experiment tracking, hyper-parameter tuning, and deploying automated model retraining pipelines. Programming ...

Science agenda. We are particularly interested in AI-accelerated approaches that strengthen mesoscale modelling itself, for example surrogate models, data-centric engineering, and Bayesian techniques for uncertainty quantification and addressing model mis-specification, rather than AI/ML applied without a mesoscale modelling base. Applicants should demonstrate ...

delivery, and ensure actionable insights reach senior stakeholders and C-suite executives. You will build dashboards, apply econometrics and Bayesian methods, and translate complex results into practical recommendations, driving ROI and client success. Hybrid work with a central London base. #J-18808-Ljbffr ...

Secondmind Labs is seeking a PhD-level researcher to advance probabilistic modelling, Bayesian optimization, and related fields. You will work in collaborative research teams to develop scalable algorithms addressing real-world problems for customers. You will publish papers, contribute to open-source libraries, and help shape ...

duties and responsibilities will include, but won't be limited to building and improving sports prediction modelsTo research recent advances in Bayesian updating to better extract signals from noisy dataTo design and build your own models using your own ideasTo work closely with expert traders and developers ...

Statistics, Mathematics, Physics, or similar. You reason about uncertainty and calibration as first-order concerns. Research mindset. You're curious about new methods and actively look for better ways to do things. You try them out, not just read about them. Judgement. You critically evaluate model output – yours … experiments, or lift studies. Marketing mix or attribution modelling. You have used or contributed to models that quantify channel impact or optimise spend. Bayesian methods. You have used hierarchical models, MCMC, or Bayesian updating in real work. Production ML. You have built and shipped ...