51 to 75 of 165 Permanent Pandas Jobs

trading constraints. Automate Data Pipelines, designing and managing workflows for collecting, cleaning, and storing large volumes of financial data (e.g., price, volume, fundamentals, alternative data), often using tools like Pandas, NumPy, and Dask. Collaborate Across Teams for Deployment, working with researchers, traders, and DevOps teams to integrate Python models into production environments (e.g., through APIs, microservices, or containerized systems like More ❯

monitoring. Requirements Must Have: 5+ years of professional Python development experience. Strong ability to write clean, modern Python code. Experience building and documenting APIs. Deep knowledge of Python ecosystem (Pandas, Numpy, Bokeh, PyArrow, Matplotlib, IPyWidgets, Jupyter, etc.). Proven experience with large-scale data pipelines and ETL workflows. Comfortable working in Jupyter notebooks. Understanding of crypto or traditional financial markets. More ❯

Experience Strong expertise in AI/ML, LLMs (GPT, Claude) and Generative AI . Proven experience with Agentic AI tools, GitHub Copilot, MCPs . Advanced Python skills – NLTK, NumPy, Pandas, Scikit-learn. Good understanding of AI/ML algorithms (Regression, Classification, Decision Trees, KNN, K-Means). Experience developing AI-enhanced test automation solutions. Solid grasp of SQL . Strong More ❯

the latest developments in AI, machine learning, and data science methodologies. Experienced Needed: Masters or PhD in a STEM subject Proficiency in Python, with experience in libraries such as pandas, scikit-learn, TensorFlow, or PyTorch. Solid SQL skills and experience working with relational databases. Exposure to cloud platforms (AWS, GCP, or Azure) would be advantageous. Strong analytical and problem-solving More ❯

4+ years of software engineering experience. Must be open to obtaining and maintaining a U.S. government security clearance. Proficiency in Python with a solid understanding of Python Data Stack (pandas, NumPy, scikit-learn, PyTorch, Matplotlib, etc.). Proven track record of deploying software into production environments. Familiarity with Docker, Kubernetes, and Git. Exceptional problem-solving skills and a keen sense More ❯

expertise in MLOps implementation for deploying, monitoring, and managing ML models in production environments. Proficiency in Python and experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy Strong understanding of cloud technologies and AI/ML platforms, particularly AWS SageMaker. Solid grasp of software engineering principles including design patterns, testing, CI/CD, security, and version More ❯

GeoPandas, Shapely, and GDAL Knowledge of PostgreSQL/PostGIS for spatial data management Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and data science tools (e.g., Jupyter, Pandas, NumPy) Ability to design, train, and evaluate supervised and unsupervised learning algorithms Experience working with large datasets, including data preprocessing Excellent communication skills, both written and verbal English, with the More ❯

models across domains such as natural language processing, computer vision, or predictive analytics Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and data science tools (e.g., Jupyter, Pandas, NumPy) Ability to design, train, and evaluate supervised and unsupervised learning algorithms Strong teamwork and interpersonal skills, with a collaborative and agile mindset Proven ability to work within agile development More ❯

master’s degree in a STEM subject (Mathematics, Computer Science or Engineering) Experience working in a data science or consulting role In-depth experience of working with Python and Pandas An entrepreneurial spirit and drive to work in an early stage start-up A curious mindset to understand how we can improve things and better help our clients address commercial More ❯

in Visual Language Models or multimodal machine learning. Strong experience with machine learning libraries and frameworks such as PyTorch, TensorFlow, or Hugging Face. Proficiency in Python, including libraries like pandas, numpy, and scikit-learn. Solid understanding of deep learning techniques and experience with transfer learning, fine-tuning, and model evaluation. Experience with cloud platforms (e.g., AWS SageMaker) for model training More ❯

large-scale language and vision models (Transformers, GPT, VLMs). Hands-on experience with multimodal data (text, images, 3D). Proficiency in Python and key ML libraries (PyTorch, TensorFlow, pandas, NumPy). Solid grounding in probability, statistics, and optimization for generative modeling. Experience deploying ML and AI models using cloud microservice architecture (AWS preferred). Strong software engineering skills, including More ❯

large-scale language and vision models (Transformers, GPT, VLMs). Hands-on experience with multimodal data (text, images, 3D). Proficiency in Python and key ML libraries (PyTorch, TensorFlow, pandas, NumPy). Solid grounding in probability, statistics, and optimization for generative modeling. Experience deploying ML and AI models using cloud microservice architecture (AWS preferred). Strong software engineering skills, including More ❯

for specific research tasks Position Requirements: Ph.D. in Biomedical Engineering, Bioinformatics, Computational Biology, or a related field Proficiency in Python programming and experience with libraries such as NumPy, SciPy, pandas, and scikit-image Demonstrated experience in microscopy data analysis and image processing techniques Strong problem-solving skills and a track record of developing computational tools or methods Excellent communication skills More ❯

automation-ready using methodologies. Python Development - Strong proficiency in Python programming including object-oriented design, asynchronous programming, error handling, and writing clean, maintainable code. Experience with key libraries including Pandas, NumPy for data manipulation, requests and APIs for integrations, asyncio for concurrent processing, and building robust automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep More ❯

usage based preferred). Deep hands on expertise with dbt (production grade models, testing, CI/CD) and Snowflake (performance tuning, RBAC, cost management). Advanced SQL + Python (pandas, scipy/statsmodels, or Prophet) for forecasting, scenario modeling, and statistical analysis. Strong grasp of SaaS/cloud unit economics-MRR/ARR, COGS allocation, gross margin, payback, LTV/ More ❯

Working knowledge of advanced predictive modeling, optimization, scenario analysis, and statistical methodologies. Strong grasp of supervised/unsupervised methods, evaluation metrics, feature engineering, and model tuning. Proficiency in Python (pandas, NumPy, Scikit-learn); experience with PyTorch or TensorFlow for deep learning. Experience with API development and connecting AI systems to external platforms. Working knowledge in deep learning techniques, including CNNs More ❯

requiring wrangling, normalization, and tidying Proficient in writing high quality software tooling, particularly in Python and MATLAB. Deep familiarity with industry standard numerical computing toolsets such as scipy, numpy, pandas or Mathworks Statistics and Machine Learning Toolbox History of collaborative projects embedded in technical domains, especially in scientific or engineering spaces. Desire to embed themselves in high-stakes environments where More ❯

understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and data science libraries (e.g., NumPy, pandas, scikit-learn). Proficiency in Python, R, or other relevant programming languages. Proficiency in working with large datasets, data wrangling, and data preprocessing. Experience in data science, statistical modelling, and More ❯

working with Python, SQL and noSQL databases Experience with one or more data science and machine/deep learning frameworks and tooling, including scikit-learn, H2O, keras, pytorch, tensorflow, pandas, numpy, carot, tidyverse Command of data science and statistics principles (regression, Bayes, time series, clustering, P/R, AUROC, exploratory data analysis etc ) Strong knowledge of key programming concepts (e.g. More ❯

experiment tracking, model registry, MLFLow, Weights and Biases, ML Metrics and Evaluation/Quality. Distributed machine learning frameworks - PyTorch, Lightning, Ray. Model Data Curation - Parquet data processing (PyArrow, Daft, Pandas, etc). Development Tools & Eco-System (at scale) - Proficiency in Python software development. Also, VDI and cloud-based development environments, CI Systems (GitHub Actions), and Docker. Bonus Points! Data operations More ❯

Pathways The candidate will be responsible for developing reproducible pipelines for differential expression, pathway enrichment, and immune deconvolution, supporting cancer biomarker discovery and drug response analysis. Proficiency in Python (pandas, TensorFlow, MATLAB), R, and SQL (including query optimization and indexing) is required, along with experience in data cleaning, signal preprocessing, and feature extraction, with emphasis on maximizing data fidelity and More ❯

years of experience in software development and data engineering with a strong focus on data cleaning, transformation, and creation. Proficiency in Python and experience with data processing libraries (e.g., Pandas, Polars, NumPy). Hands-on experience in building and maintaining automated data pipelines for large-scale data processing. Familiarity with machine learning frameworks (e.g., PyTorch, JAX, scikit-learn) as applied More ❯

have Must be strong in Python Java and/or REXX is helpful but not a must have Data manipulation experience is a big plus - Numpy/PySpark/Pandas are a big plus IAC tools like Terraform and/or CloudFormation would be very beneficial More ❯

EMRs. Who You Are Experience: 5+ years as a Data Scientist or in a related role (experience in the healthcare industry is required). Skills: Proficiency in Python/Pandas and SQL is mandatory. Infrastructure: Familiarity with AWS or GCP is a plus. Join us to make an impact in healthcare innovation More ❯

proofs-of-concept , model monitoring , and adoption of emerging AI tech. What We’re Looking For 5+ years in data engineering, with team or project leadership experience. Advanced Python (Pandas, PyTorch, TensorFlow, Scikit-learn). Strong AWS/GCP , MySQL , and CI/CD experience; Docker/Kubernetes a plus. Excellent communication, organisation, and problem-solving skills. Passion for innovation More ❯