226 to 250 of 302 Permanent Pandas Jobs

Experience with data management, including storage and retrieval technologies. Preferred Qualifications Familiarity with Objective Simulation Framework (OSF) and HWIL architecture. Experience with Linux and Python data analysis libraries (e.g., Pandas, NumPy). Basic understanding of AI/ML concepts. Experience with data visualization tools (e.g., Tableau, Power BI). Demonstrated understanding of the Missile Defense System Schedule: Mon-Fri More ❯

and model evaluation Experience in SQL and Python for advance analytics and modelling (experience with Snowflake, R, GitHub, and Jira is a plus) Experience using Python libraries such as pandas, scikit-learn, and statsmodels (or R equivalent) Experience using BI tools like Power BI or Tableau to communicate insights Experience mentoring or upskilling colleagues in analytics tools (such as SQL More ❯

and model evaluation Experience in SQL and Python for advance analytics and modelling (experience with Snowflake, R, GitHub, and Jira is a plus) Experience using Python libraries such as pandas, scikit-learn, and statsmodels (or R equivalent) Experience using BI tools like Power BI or Tableau to communicate insights Experience mentoring or upskilling colleagues in analytics tools (such as SQL More ❯

space domain data DoD 8570 IAT Level II certification (e.g., Security+ CE, CCNA-Security) Robust knowledge of orbital mechanics Experience with applying Python numerical and libraries such as NumPy, Pandas, Matplotlib, SciPy, etc. Excellent problem solving and critical thinking skills, with a track record of resolving complex orbital anomalies Familiarity with Linux-based OS, particularly Red Hat or Suse. Proficiency More ❯

an agile cross functional setup and with a broad range of partners. Proficiency with Python (or similar languages) and its libraries for machine learning such as PySpark, scikit-learn, pandas and pytorch. Prior experience with general software development practices including code management (Git) and testing. Collaborative spirit and a playful can-do attitude. Persistent with a well-rounded view on More ❯

Vision, or related technical discipline. Good knowledge of machine learning and computer vision algorithms. Familiarity with real-time imaging pipelines. Experience with scientific software packages such as PyTorch, OpenCV, Pandas, SciPy, NumPy, SciKit's, etc. Experience in standard software engineering practices including version control systems and software testing methodologies. Excellent oral and written communication skills. Analytical thinker, attentive to details More ❯

mission stakeholders. Required Qualifications: Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. Experience with Python and common data science libraries (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Ability to interpret and communicate complex analytic results to non-technical audiences. Strong understanding of data wrangling, model training, and evaluation techniques. Desired Qualifications: Familiarity More ❯

mission stakeholders. Required Qualifications: Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. Experience with Python and common data science libraries (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Ability to interpret and communicate complex analytic results to non-technical audiences. Strong understanding of data wrangling, model training, and evaluation techniques. Desired Qualifications: Familiarity More ❯

and have in-depth knowledge of how they work Python: You have built and deployed production-grade Python applications and you are familiar with data science libraries such as pandas and scikit-learn Tooling & Environment : DevOps: You have experience working with DevOps tooling, such as gitops, Kubernetes, CI/CD tools (we use buildkite) and Docker Cloud: You have worked More ❯

GIS, ArcGIS), remote sensing techniques, and the application of data science in the IC. Expert proficiency in Python (or similar languages) and experience with data science libraries (TensorFlow, PyTorch, Pandas, NumPy). Strong experience with big data processing tools (e.g., Spark, Hadoop, AWS or Azure cloud platforms). Expertise in working with geospatial data formats (e.g., GeoTIFF, Shapefiles, WMS, WFS More ❯

GIS, ArcGIS), remote sensing techniques, and the application of data science in the IC. Expert proficiency in Python (or similar languages) and experience with data science libraries (TensorFlow, PyTorch, Pandas, NumPy). Strong experience with big data processing tools (e.g., Spark, Hadoop, AWS or Azure cloud platforms). Expertise in working with geospatial data formats (e.g., GeoTIFF, Shapefiles, WMS, WFS More ❯

designing and deploying ArcGIS Enterprise in multi-environment configurations.Required8Years? Proficiency in DNS, port assignment, and firewall policy management related to ArcGIS Server and ArcGIS Enterprise.Required8Years? Proficiency using Python (ArcPy, Pandas) and SQL for ArcGIS management and automation.Required8Years? Demonstrated experience with geodatabase design and spatial analysis.Required8Years? Familiarity with GIS web services (REST, SOAP) and APIs.Required8Years? Familiarity with Esri?s current licensing More ❯

not possible or desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as More ❯

not possible or desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as More ❯

not possible or desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as More ❯

not possible or desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as More ❯

not possible or desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as More ❯

databases and dashboarding software such as Power BI or Tableau is important. Familiarity with programming languages such as Python or R and their associated data analysis libraries (e.g., NumPy, Pandas, scikit-learn) is a plus. Statistical Expertise: Strong understanding of statistics, including descriptive statistics, regression, probability, sampling, and hypothesis testing. Communication: Excellent written and verbal presentation skills, with the ability More ❯

Apply statistical methods, machine learning, and predictive modeling to identify patterns, anomalies, and potential risks. Write clean, efficient, and well-documented code in Python leveraging data science libraries (e.g., pandas, NumPy, scikit-learn, PyTorch, TensorFlow). Query, manipulate, and analyze structured and unstructured data from databases (SQL, NoSQL, Hive, etc.). Support data ingestion, processing, and visualization workflows to deliver More ❯

Python, FastAPI, MongoDB, cloud-native) Ensure observability, security, and compliance (HIPAA, HITECH) What You Bring 8+ years in software/data engineering; 3+ years with distributed systems Strong Python (Pandas, PySpark, FastAPI), Prefect/Airflow experience Familiarity with containerized environments (Docker, K8s, CI/CD) Experience with or interest in healthcare data standards (FHIR, HL7) Strong problem-solving, communication, and More ❯

part in design and architecture discussions. About you Master’s or PhD in AI, Machine Learning, Data Science, or Computer Science (Russell Group or similar). Strong Python skills (Pandas, NumPy). Experience or exposure to NLP, transformers, and LLMs. Familiarity with ML tools like Weights & Biases or MLflow is a plus. Curious, proactive, and confident working independently. Ideally based More ❯

part in design and architecture discussions. About you Master’s or PhD in AI, Machine Learning, Data Science, or Computer Science (Russell Group or similar). Strong Python skills (Pandas, NumPy). Experience or exposure to NLP, transformers, and LLMs. Familiarity with ML tools like Weights & Biases or MLflow is a plus. Curious, proactive, and confident working independently. Ideally based More ❯

part in design and architecture discussions. About you Master’s or PhD in AI, Machine Learning, Data Science, or Computer Science (Russell Group or similar). Strong Python skills (Pandas, NumPy). Experience or exposure to NLP, transformers, and LLMs. Familiarity with ML tools like Weights & Biases or MLflow is a plus. Curious, proactive, and confident working independently. Ideally based More ❯

part in design and architecture discussions. About you Master’s or PhD in AI, Machine Learning, Data Science, or Computer Science (Russell Group or similar). Strong Python skills (Pandas, NumPy). Experience or exposure to NLP, transformers, and LLMs. Familiarity with ML tools like Weights & Biases or MLflow is a plus. Curious, proactive, and confident working independently. Ideally based More ❯

part in design and architecture discussions. About you Master’s or PhD in AI, Machine Learning, Data Science, or Computer Science (Russell Group or similar). Strong Python skills (Pandas, NumPy). Experience or exposure to NLP, transformers, and LLMs. Familiarity with ML tools like Weights & Biases or MLflow is a plus. Curious, proactive, and confident working independently. Ideally based More ❯