rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable working More ❯
rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable working More ❯
rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable working More ❯
Stevenage, Hertfordshire, UK Hybrid/Remote Options
Crossing Hurdles
rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable working More ❯
rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable working More ❯
rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable working More ❯
Cambridge, Cambridgeshire, UK Hybrid/Remote Options
Crossing Hurdles
rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable working More ❯
Peterborough, Cambridgeshire, UK Hybrid/Remote Options
Crossing Hurdles
rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable working More ❯
rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable working More ❯
rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable working More ❯
rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable working More ❯
Hemel Hempstead, Hertfordshire, UK Hybrid/Remote Options
Crossing Hurdles
rubric structure, and evaluation criteria. Communicate insights to data labeling experts and technical teams. Requirements Strong foundation in statistical analysis, hypothesis testing, and pattern recognition. Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis. Experience with exploratory data analysis and deriving actionable insights from complex datasets. Familiarity with LLM evaluation methods and quality metrics. Comfortable working More ❯
be a PhD holder in electronics, physics or computer science and have significant skills and experience in the following areas: - Expert Python proficiency for data analysis and prototyping (NumPy, SciPy, PyTorch). - Demonstrable applied experience of digital signal processing (FFT, modulation, noise modelling, resampling). - Experience with SDR frameworks (GNU Radio, SDRangel, SoapySDR). - Understanding of RF hardware (antenna, filters More ❯
Cambridge, Cambridgeshire, England, United Kingdom
Adria Solutions
improve signal integrity and inference accuracy Developing ML and statistical models for RF classification, anomaly detection, and emitter identification Prototyping real-time or batch-processing systems in Python (NumPy, SciPy, PyTorch) with potential integration via ZMQ, GNU Radio, or C++ backends Leading RF data collection, field experiments, and over-the-air testing using drones, wireless devices, and custom transmitters Requirements … Strong Python proficiency for RF data analysis and prototyping (NumPy, SciPy, matplotlib, scikit-learn, PyTorch) Solid understanding of DSP fundamentals (FFT, filtering, modulation, correlation, noise modelling, resampling) Familiarity with SDR frameworks such as GNU Radio, SDRangel, osmoSDR, or SoapySDR Practical understanding of RF hardware chains (antenna filters mixers ADC) and their impact on baseband data Experience analysing wireless protocols (Wi More ❯
Cambridge, Cambridgeshire, East Anglia, United Kingdom
Adria Solutions
improve signal integrity and inference accuracy Developing ML and statistical models for RF classification, anomaly detection, and emitter identification Prototyping real-time or batch-processing systems in Python (NumPy, SciPy, PyTorch) with potential integration via ZMQ, GNU Radio, or C++ backends Leading RF data collection, field experiments, and over-the-air testing using drones, wireless devices, and custom transmitters Requirements … Strong Python proficiency for RF data analysis and prototyping (NumPy, SciPy, matplotlib, scikit-learn, PyTorch) Solid understanding of DSP fundamentals (FFT, filtering, modulation, correlation, noise modelling, resampling) Familiarity with SDR frameworks such as GNU Radio, SDRangel, osmoSDR, or SoapySDR Practical understanding of RF hardware chains (antenna ? filters ? mixers ? ADC) and their impact on baseband data Experience analysing wireless protocols (Wi More ❯
