176 to 200 of 214 Remote NumPy Jobs

interpretability, and business relevance. Requirements Extensive experience in building and deploying Marketing Mix Models, with a strong focus on Bayesian methods. Expert-level proficiency in Python, especially with pandas, NumPy, and probabilistic programming libraries such as PyMC. Experience with R is a bonus, particularly for MMM-related workflows. Deep understanding of regression modelling, Bayesian inference, hierarchical models, and MCMC techniques. More ❯

interpretability, and business relevance. Requirements Extensive experience in building and deploying Marketing Mix Models, with a strong focus on Bayesian methods. Expert-level proficiency in Python, especially with pandas, NumPy, and probabilistic programming libraries such as PyMC. Experience with R is a bonus, particularly for MMM-related workflows. Deep understanding of regression modelling, Bayesian inference, hierarchical models, and MCMC techniques. More ❯

interpretability, and business relevance. Requirements Extensive experience in building and deploying Marketing Mix Models, with a strong focus on Bayesian methods. Expert-level proficiency in Python, especially with pandas, NumPy, and probabilistic programming libraries such as PyMC. Experience with R is a bonus, particularly for MMM-related workflows. Deep understanding of regression modelling, Bayesian inference, hierarchical models, and MCMC techniques. More ❯

interpretability, and business relevance. Requirements Extensive experience in building and deploying Marketing Mix Models, with a strong focus on Bayesian methods. Expert-level proficiency in Python, especially with pandas, NumPy, and probabilistic programming libraries such as PyMC. Experience with R is a bonus, particularly for MMM-related workflows. Deep understanding of regression modelling, Bayesian inference, hierarchical models, and MCMC techniques. More ❯

LOOKING FOR: 2+ years of experience as a Data Analyst or Data Scientist in IT companies. Proficiency in SQL (BigQuery experience is a plus). Solid Python knowledge (pandas, numpy at least intermediate level). Strong knowledge of statistics and probability theory. Experience with A/B testing analysis. Experience building analytical models. Understanding of cohort analysis approaches. Analytical thinking More ❯

Write clean, maintainable, and well-documented code Share ideas to improve and evolve our data platform What You Bring Proficiency in Python, SQL, and ML libraries (e.g., SKLearn, XGBoost, Numpy) Strong statistical reasoning and analytical mindset Ability to explain complex concepts to diverse stakeholders Self-starter attitude with curiosity and drive A degree in Data Science, Math, Statistics, or Computer More ❯

Scientist, your background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression More ❯

Scientist, your background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression More ❯

Scientist, your background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression More ❯

Scientist, your background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression More ❯

Scientist, your background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression More ❯

Scientist, your background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression More ❯

We’re Looking For: At least 1 year in a Data Science role, with practical experience applying machine learning techniques. Proficiency in Python, with experience using libraries like pandas, NumPy, scikit-learn, and PyTorch. A relentless drive to push model performance boundaries, a focus on client needs, and a dedication to delivering impactful results. Familiarity with NLP concepts, transformer models More ❯

skills, including the ability to challenge hypotheses, analyze and structure data, draw conclusions, and interrelate data. Proficiency in mathematical statistics and practical experience applying it. Confidence using Python (Pandas, NumPy) and experience with SQL. Ability to determine the appropriate approach to data assessment: analytics, research, or leveraging external data. At least one year of experience in data analysis or a More ❯

initiatives. Requirements You have a strong ability to analyze and interpret large datasets, uncovering meaningful trends and insights. You are proficient in SQL and experienced in using Python (pandas, numpy, matplotlib, seaborn) for exploratory data analysis and data visualization. Big plus is practical familiarity with the big data stack (Spark, Presto/Athena, Hive). You have experience with BI More ❯

XLOOKUP, macros) Experience with Power BI/Fabric Strong problem-solving and critical thinking abilities Excellent communication skills and stakeholder engagement experience Familiarity with Python for data analysis (pandas, NumPy, etc.) - desirable Understanding of data warehousing, ETL, and data governance - desirable Degree in a STEM subject - nice to have Knowledge of the energy/utilities sector - a bonus Benefits include More ❯

exciting business. 12 months to 3 years of AI experience in AI/ML projects - ideally working on business solutions and workflows. Proficient with Python and libraries such as NumPy, Pandas, and one or more ML frameworks (e.g., Scikit-learn, TensorFlow, or PyTorch). Understanding of how machine learning models are trained, evaluated, and deployed. Exposure to cloud platforms (especially More ❯

comprehensive documentation for AI/ML pipelines, data workflows, and analytical processes. Your skills and experience 5+ years of experience in data science. Experience with data science libraries (e.g., NumPy, pandas, scikit-learn). Proficiency in working with large datasets, data wrangling, and data preprocessing. Experience in data science, statistical modelling, and data analytics techniques. Experience with data analysis and More ❯

collaborative skills. Good understanding of data structures, software architecture, and data modeling. Experience with tabular data, computer vision, imagery, point clouds, and game datasets. Proficiency with ML libraries like NumPy, OpenCV, scikit-learn, PyTorch/PyTorch3D, TensorFlow, Keras; familiarity with CI/CD, version control (GitLab, Perforce), and cloud platforms (preferably AWS). Benefits include: 22 days holidays + Christmas More ❯

initiatives. Requirements You have a strong ability to analyze and interpret large datasets, uncovering meaningful trends and insights. You are proficient in SQL and experienced in using Python (pandas, numpy, matplotlib, seaborn) for exploratory data analysis and data visualization. A big plus is practical familiarity with the big data stack (Spark, Presto/Athena, Hive). You have experience with More ❯

of experience developing and deploying 3D vision or spatial AI systems in production or real-world settings. Proficiency in Python, and familiarity with machine learning libraries such as PyTorch, NumPy, Pandas, and others. Deep understanding of evaluation methodologies for deep learning and spatial perception systems (e.g., metrics, validation strategies, ablations). Hands-on experience with SLAM/SfM systems using More ❯

using Power BI or similar tools, with expertise in connecting and integrating data sets for accurate and comprehensive analysis Proficiency in using common data science Python packages (e.g. Pandas, NumPy, Scikit-learn and Matplotlib) for data manipulation, analysis, and visualisation Familiarity with advanced data science techniques, including machine learning (e.g., K-means), natural language processing (e.g., NLTK or spaCy), and More ❯

and deduplication, adept at transforming raw data into a unified and reliable asset. Projects natural confidence in communication and has strong stakeholder management skills. Has strong proficiency with Pandas, Numpy, PySpark or similar for Data Analysis & Cleaning Python Maintains a solid knowledge of both Automation tools, & other emerging technologies including AI platforms & LLM's. Organised, meticulous & attention to detail orientated More ❯

you up for success. These include: Understanding of machine learning tools and visualisation techniques (e.g.PowerBI) to produce solutions to problems. Proficient in Python using data science libraries such as Numpy, Pandas, scikit-learn, and Plotly. Basic knowledge of SQL and Git for version control. A qualification in Data Science or a related field. Good communication skills, adaptable and proactive approach. More ❯

doctoral roles, a proven track record of publications, or contributions to machine learning codebases. Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas Strong knowledge of linear algebra, calculus and statistics Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics) Experience working with biological or chemical data More ❯