176 to 200 of 277 Remote Pandas Jobs

A proactive approach to problem-solving and collaboration, with the ability to work closely with technical and non-technical teams. Desired Skills Python expertise, especially with data libraries like Pandas, NumPy, and Scikit-learn. Familiarity with ETL tools and data pipeline orchestration. Exposure to data science tools like SAS or Posit. Experience in performance-critical environments, particularly with large-scale More ❯

as convolutional neural networks, recurrent neural networks, transformer architectures, decision trees, boosting, etc. Good programming knowledge in Python and its math & machine learning packages such as numpy, scikit-learn, pandas/dask, tensorflow/keras, pytorch, etc Experience in developing and deploying machine learning models in a real production environment Experience with Large Language Models and Generative AI is valued More ❯

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 visualization More ❯

team and actively contribute to regular agile ceremonies, with your workflow supported by Jira. Qualifications Skill requirements: • At least 3 years of programming with Python, including extensive experience with Pandas for data manipulation and analysis • Solid understanding of Hadoop ecosystem • Ability to analyze complex datasets and extract actionable insights • ETL pipeline development • Familiarity with machine learning workflows Optional skills: • Hands More ❯

and performance of a potential solution Comprehensive knowledge of software engineering, programming fundamentals and industry experience using Python Experience with data manipulation and processing, such as SQL, Cypher or Pandas A can-do proactive and assertive attitude - your manager believes in freedom and responsibility and helping you own what you do; you will excel best if this environment suits you More ❯

OLAP) systems Creating conceptual, logical and physical data models Creating mapping specifications for data migrations Coordinating User Acceptance Testing (UAT) with business stakeholders Excellent SQL skills Knowledge of python (pandas) Experience with Cloud platforms Creating data dashboards using Tableau, PowerBI or Qlik and story telling We expect you to work closely with business to understand their current data problems, pain More ❯

Master's degree in Computer Science, Mathematics, Statistics, or a related field. Strong understanding of probability, statistics, and linear algebra. Proficiency in Python, including libraries such as scikit-learn, pandas, seaborn, and matplotlib. Experience writing and optimising SQL queries for data retrieval and manipulation. Ability to communicate complex insights in a simple and effective manner. Detail-oriented with a strong More ❯

solutions, capable of the following: Recommended: 2+ years of professional experience in a data engineering or similar role. Proficiency in Python , including use of libraries for data processing (e.g., pandas, pySpark). Experience working with Azure-based data services , particularly Azure Databricks , Data Factory, and Blob Storage. Demonstrable knowledge of data pipeline orchestration and optimisation. Understanding of SQL for data More ❯

understanding of machine learning, deep learning, and other AI techniques. Proficiency in Python and relevant AI libraries (e.g., TensorFlow, PyTorch). Experience with data processing and analysis tools (e.g., Pandas, SQL). Experience with cloud platforms such as Amazon Web Services, Azure, or Google Cloud Platform. Ability to work with version control systems (e.g., Git). Excellent communication and problem More ❯

to write pipelines to load millions of records. Advanced skills in writing highly optimized SQL code. Experience with relational databases Snowflake or Oracle is preferred. Python work experience with Pandas, Numpy and Scikit Ability to communicate and interact with a wide range of data users – from very technical to non-technical. Team player who is execution focused, with the able More ❯

engineering, mathematics, physics, statistics Experience of data science in finance, insurance or Ecommerce is an advantage but not required. Experience with neural networks and Tensor Flow, CatBoost, XGBoost, SKlearn, Pandas If you hold the experience and technical skills outlined above which would enable you to hit the ground running, please apply to find out more information about this exciting opportunity. More ❯

engineering, mathematics, physics, statistics ??Experience of data science in finance, insurance or Ecommerce is an advantage but not required. ??Experience with neural networks and Tensor Flow, CatBoost, XGBoost, SKlearn, Pandas If you hold the experience and technical skills outlined above which would enable you to hit the ground running, please apply to find out more information about this exciting opportunity. More ❯

not important, we do require the ability to become a fluent Python programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of More ❯

of their activities Provable knowledge of at least one of the following languages or equivalents: Python, R, Scala, Java Experience with common data science toolkits, such as scikit-learn, pandas, R, Weka; excellence in more than one of these is highly desirable Good understanding of SQL and NoSQL (plus) database technologies; understanding of big data technologies: Hadoop, Spark (plus) Good More ❯

of their activities Provable knowledge of at least one of the following languages or equivalents: Python, R, Scala, Java Experience with common data science toolkits, such as scikit-learn, pandas, R, Weka; excellence in more than one of these is highly desirable Good understanding of SQL and NoSQL (plus) database technologies; understanding of big data technologies: Hadoop, Spark (plus) Good More ❯

marketing, or product-focused roles. Understanding of LTV modeling, forecasting, and experimental design. Comprehension of A/B testing methodologies Proficiency in Python for data analysis and modeling (e.g., pandas, scikit-learn, statsmodels). Strong SQL skills and experience working with large datasets in modern data environments. Experience working with cross-functional growth or marketing teams. Competent user of data More ❯

guardrails for Generative AI applications Skills in Python and SQL for data science, including how to write modular code, familiarity with the core Python data structures and fluency with pandas and other packages commonly used for data science. Strong ability to coach data scientists in how to use these tools to address particular business problems and to review the code More ❯

understanding of machine learning, deep learning, and other AI techniques. Proficiency in Python and relevant AI libraries (e.g., TensorFlow, PyTorch). Experience with data processing and analysis tools (e.g., Pandas, SQL). Experienced with cloud platforms such as Amazon Web Services, Azure, or Google Cloud Platform. Ability to work with version control systems (e.g., Git). Excellent communication and problem More ❯

Ideally, >2 years of experience in a data-driven role, with exposure to: building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications; developing models for bespoke problem settings that involve high-dimensional data (spatiotemporal, geometric, physical); iterating on network architectures and model structure, tuning and More ❯

understanding of machine learning, deep learning, and other AI techniques. Proficiency in Python and relevant AI libraries (e.g., TensorFlow, PyTorch). Experience with data processing and analysis tools (e.g., Pandas, SQL). Experienced with cloud platforms such as Amazon Web Services, Azure, or Google Cloud Platform. Ability to work with version control systems (e.g., Git). Excellent communication and problem More ❯

via automated ML Ops. Ideally, you’ll also be technically skilled in most or all of the below: Expert knowledge of Python and SQL, inc. the following libraries: Numpy, Pandas, PySpark and Spark SQL Expert knowledge of ML Ops frameworks in the following categories: experiment tracking and model metadata management (e.g. MLflow) orchestration of ML workflows (e.g. Metaflow) data and More ❯

degree in sciences and further post-graduate study in mathematics, statistics or related field or equivalent industry experience. Experience with Python and SQL, including key packages such as Numpy, Pandas and Scikit-learn Have experience with implementation of machine learning concepts and methods Have a solid knowledge of statistical concepts and their applications Have great communication skills with a passion More ❯

marketing, or product-focused roles. Understanding of LTV modeling, forecasting, and experimental design. Comprehension of A/B testing methodologies Proficiency in Python for data analysis and modeling (e.g., pandas, scikit-learn, statsmodels). Strong SQL skills and experience working with large datasets in modern data environments. Experience working with cross-functional growth or marketing teams. Competent user of data More ❯

in data science, ideally in growth, marketing, or product-focused roles. Deep understanding of LTV modeling, forecasting, and experimental design. Proficiency in Python for data analysis and modeling (e.g., pandas, scikit-learn, statsmodels). Advanced SQL skills and experience working with large datasets in modern data environments. Experience working with cross-functional growth or marketing teams. Competent user of data More ❯

engineers, data analytics/scientists on the development of analytics, insight and marketing model development. Data manipulation, cleaning and analysis : Proficient in data manipulation and analysis using tools like Pandas, NumPy, and SQL. Ability to work with large-scale datasets and extract meaningful insights. Experience in data processing to enable accurate analytics as well as effective model creation.. Ability to More ❯