376 to 400 of 622 Pandas Jobs

Statistics, Engineering). 3+ years of professional experience in Data Science or Quantitative roles within finance. Proficiency in Python and SQL with exp. in data processing libraries such as pandas/numpy. Experience with machine learning frameworks and statistical analysis tools. Familiarity with financial data sources, APIs, and data modelling techniques. Ability to design, implement, and maintain scalable data pipelines More ❯

language modeling, and semantic similarity. Strong proficiency in Python, including use of ML libraries such as TensorFlow, PyTorch, or similar. Experience with data science tools and platforms (e.g., Jupyter, Pandas, NumPy, MLFlow). Familiarity with cloud-based AI tools and infrastructure, especially within the AWS ecosystem. Strong understanding of data structures, algorithms, and statistical analysis. Experience working with ETL pipelines More ❯

language modeling, and semantic similarity. Strong proficiency in Python, including use of ML libraries such as TensorFlow, PyTorch, or similar. Experience with data science tools and platforms (e.g., Jupyter, Pandas, NumPy, MLFlow). Familiarity with cloud-based AI tools and infrastructure, especially within the AWS ecosystem. Strong understanding of data structures, algorithms, and statistical analysis. Experience working with ETL pipelines More ❯

Must-Have Skills Solid experience with data engineering on AWS (Glue, S3) Strong knowledge of Elasticsearch (query design, aggregations, performance tuning...) Proficiency in Python, especially in data wrangling (PySpark, Pandas) Experience with data quality, schema evolution, and operational monitoring Familiarity with LLMs, embeddings, or search ranking improvements is a plus Why Instantly.ai? High-growth environment: join us on the path More ❯

NLP or Computer Vision Solid understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders etc.) Extensive experience with pytorch, numpy, pandas Knowledge of open source datasets and benchmarks in NLP/Computer Vision Hands-on experience in implementing distributed/multi-threaded/scalable applications (incl. frameworks such as Ray, Horovod More ❯

unsupervised learning, and familiarity with GenAI and LLMs is a plus. Software development skills: Strong Python skills and ability to collaborate with engineers. Data manipulation and analysis: Proficiency with Pandas, NumPy, SQL, handling large datasets, and ensuring data quality. Collaborative team player: Strong communication skills and ability to work cross-functionally. Continuous learning and adaptability: Commitment to staying current with More ❯

Experience deploying and managing applications using Azure and Docker. Familiarity with frameworks such as LangChain and expertise in Retrieval-Augmented Generation (RAG) models for AI-driven applications. Proficiency with pandas for data manipulation. Full Stack Developer - What's in it for you? Salary Reviews: Twice a year to recognise your contributions. Generous Annual Leave: Enjoy 25 days plus three days More ❯

skills & experiences: You have a bachelor or university degree or equivalent by experience. A post-graduate is an asset; Strong programming skills, particularly in languages such as Python (PySpark, Pandas), SQL, ; You have knowledge of big data principles (such as distributed processing); You have an understanding of data management principles, data architecture design patterns, and data modelling techniques; You possess More ❯

science related field (e.g. machine learning, statistics, mathematics) Proficiency in statistical data modelling techniques. Proficiency with Python, including experience with statistics/machine learning packages such as scikit-learn, pandas, numpy, etc. Good SQL/data manipulation skills required including cleaning and managing data. Experience in data visualisation and communication. Experience with working with raw datasets and perform data wrangling More ❯

disciplines: Natural Language Processing (NLP) ML (e.g., Random Forests, CatBoost, LXGM) Image Recognition Optical Character Recognition (OCR) Motion Capture Proficiency in Python, R, or C++, including relevant libraries (numpy, pandas, matplotlib, scikit-learn, tensorflow, etc.). Proficiency in database protocols (e.g., SQL, noSQL). Developing testing routines or procedures. Building customer and stakeholder relationships. Supporting and leading the authoring of More ❯

and statistics Excellent communication skills through written reports and presentations Organisational skills (e.g. planning, time management) Excellent Python, including relevant libraries for data analysis and machine learning (e.g. sklearn, Pandas, NumPy) and at least one deep learning framework Strong SQL for data analysis and manipulation Strong problem-solving and analytical skills, with high attention to detail Ability to think strategically More ❯

Statistics, Engineering). 3+ years of professional experience in Data Science or Quantitative roles within finance. Proficiency in Python and SQL with exp. in data processing libraries such as pandas/numpy. Experience with machine learning frameworks and statistical analysis tools. Familiarity with financial data sources, APIs, and data modelling techniques. Ability to design, implement, and maintain scalable data pipelines More ❯

science related field (e.g. machine learning, statistics, mathematics) Proficiency in statistical data modelling techniques. Proficiency with Python, including experience with statistics/machine learning packages such as scikit-learn, pandas, numpy, etc. Good SQL/data manipulation skills required including cleaning and managing data. Experience in data visualisation and communication. Experience with working with raw datasets and perform data wrangling More ❯

strong foundation in statistics, probability, and machine learning fundamentals - either through a STEM degree, formal training, or self-study. Fluency in Python and SQL, including experience with libraries like Pandas, Scikit-learn, or equivalent. Demonstrated ability to solve real-world problems pragmatically using data. Clear, structured communication - especially the ability to explain complex topics simply. A growth mindset: curious, driven More ❯

relevant libraries. Data Engineering: Strong skills in building and managing robust data pipelines for biomedical signals, preprocessing noisy, high-dimensional neurodata, and handling large-scale datasets using tools like Pandas, NumPy, SciPy, MNE, and TensorFlow/Keras or PyTorch. Wearables: Understanding of how AI models interact with wearable biosensors, embedded systems, and real-time decoding architectures. Familiarity with challenges in More ❯

development-ready Python codebases. Produce visualizations and client-facing presentations. Collaborate with engineers and other teams to deliver solutions. Capabilities 2+ years relevant work experience. Proficient in Python (e.g., pandas, scikit-learn). Strong communication skills. Detail-oriented, with a desire to learn. Familiarity with Agile, Jira, and Confluence. Proficiency working with AWS cloud services is required. Mid-Level Data More ❯

academic field Strong python programming skills as evidenced by earlier work in data science or software engineering. 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 ❯

subject matter expert for machine learning techniques, aiding real-world problem solutions. Mentor and coach less experienced colleagues. Skills, Knowledge, and Expertise Strong proficiency in Python, including libraries like Pandas, NumPy, TensorFlow, and PyTorch. Experience with Generative AI, LLMs, and their practical applications. Expertise in data insights, analytics, and predictive modelling. Knowledge of cloud-based data platforms and infrastructure. Familiarity More ❯

requisite for reasons of National Security). The Application Engineer must be competent in the use of the following technologies: Strong Python coding skills Experience of Flask, SQLAlchemy and Pandas for their Applications. Good understanding of Microsoft Azure with Terraform for their Cloud Services desirable but not essential. Docker for containerising their deployed applications or similar. GitHub for Code Versioning More ❯

development-ready Python codebases. Produce visualizations and client-facing presentations. Collaborate with engineers and other teams to deliver solutions. Capabilities 2+ years relevant work experience. Proficient in Python (e.g., pandas, scikit-learn). Strong communication skills. Detail-oriented, eager to learn. Familiarity with Agile, Jira, and Confluence. Proficiency with AWS cloud services. Mid-Level Data Scientist Responsibilities Lead workstreams from More ❯

development-ready Python codebases. Produce visualizations and client-facing presentations. Collaborate with engineers and other teams to deliver solutions. Capabilities 2+ years relevant work experience. Proficient in Python (e.g., pandas, scikit-learn). Strong communication skills. Detail-oriented, with a desire to learn. Familiarity with Agile, Jira, and Confluence. Proficiency with AWS cloud services. Mid-Level Data Scientist Responsibilities Lead More ❯

development-ready Python codebases. Produce visualizations and client-facing presentations. Collaborate with engineers and other teams to deliver solutions. Capabilities 2+ years relevant work experience. Proficient in Python (e.g., pandas, scikit-learn). Strong communication skills. Detail-oriented, eager to learn. Familiarity with Agile, Jira, and Confluence. Proficiency with AWS cloud services is required. Mid-Level Data Scientist Responsibilities Lead More ❯

development-ready Python codebases. Produce visualisations and client-facing presentations. Collaborate with engineers and other teams to deliver solutions. Capabilities 2+ years relevant work experience. Proficient in Python (e.g., pandas, scikit-learn). Strong communication skills. Detail-oriented, with a desire to learn. Familiarity with Agile, Jira, and Confluence. Proficiency with AWS cloud services. Mid-Level Data Scientist Responsibilities Lead More ❯

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 ❯

relationship management experience Battery-specific origination or analysis experience Experience in spot/real-time flexibility markets Experience with R/Python for data manipulation and big data (eg. Pandas). We encourage you to apply even if you may not meet every requirement in this posting. We value diversity and our environment is supportive, challenging and focused on the More ❯