1 to 25 of 203 Pandas Jobs

Engineering, AI, or related field. 7+ years of professional software development experience, with at least 3 years in AI/ML. Strong proficiency in Python , including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch . Solid understanding of ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . More ❯

trading Requirements: Bachelor's degree or higher in CS, Engineering or other technical discipline Demonstrated ability to program in a scientific computing environment, preferably in Python/NumPy/Pandas and Java/C++ Experience working with distributed systems and large data sets Strong knowledge of algorithms, design patterns, OOP, threading, multiprocessing, etc. Experience with SQL, NoSQL, or tick databases More ❯

Qualifications: Master's degree in Computer Science, Information Systems, Engineering, or equivalent experience in a scientific/technical discipline. Strong experience with Python and its data ecosystem (e.g., NumPy, pandas, scikit-learn). Proficiency in Java or Scala for developing scalable backend systems and data pipelines. Solid understanding of SQL and relational databases (e.g., MySQL, PostgreSQL, Hive). Familiarity with More ❯

in place of a degree Experience with the following Data Science technologies Various machine learning libraries (i.e. Apache Spark, Scikit-learn, XGBoost, etc.) Data manipulation and pipeline libraries (i.e. Pandas, Polars, matplotlib, Plotly, numpy, scipy, etc.) Data science environments (e.g. Jupyter Notebook, Data Bricks, or Amazon Sage Maker) Experience implementing the data science process, developing experiments, reporting and explaining results More ❯

IT and regulatory standards. Skills & Experience Strong proficiency in Python, with a focus on rapid prototyping and data driven applications. Solid understanding of multi-processing and AsyncIO. Experience with pandas, NumPy, and SQL for data analysis and transformation. Exposure to REST APIs, messaging systems, and integration with trading or risk platforms. Hands-on experience building Front End tools or GUIs. More ❯

that you work. The work space itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark, pySpark, Hadoop, Kafka, ElasticSearch More ❯

that you work. The work space itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark, pySpark, Hadoop, Kafka, ElasticSearch More ❯

to undertake a contract assignment. In order to be successful, you will have the following experience: Extensive AI & Data Development background Experiences with Python (including data libraries such as Pandas, NumPy, and PySpark) and Apache Spark (PySpark preferred) Strong experience with data management and processing pipelines Algorithm development and knowledge of graphs will be beneficial SC Clearance is essential Within More ❯

experienced AI/Data Developer for an urgent contract assignment. Key Requirements: Proven background in AI and data development Strong proficiency in Python , including data-focused libraries such as Pandas, NumPy, and PySpark Hands-on experience with Apache Spark (PySpark preferred) Solid understanding of data management and processing pipelines Experience in algorithm development and graph data structures is advantageous Active More ❯

experienced AI/Data Developer for an urgent contract assignment. Key Requirements: Proven background in AI and data development Strong proficiency in Python , including data-focused libraries such as Pandas, NumPy, and PySpark Hands-on experience with Apache Spark (PySpark preferred) Solid understanding of data management and processing pipelines Experience in algorithm development and graph data structures is advantageous Active More ❯

processing and ML jobs, including the use of IAC to build data pipelines Expert knowledge of Python. An excellent knowledge of basic machine learning libraries, such as NumPy, SciPy, Pandas, Dask, PyTorch, Tensorflow, etc. A proven track record of linking data from multiple systems for scalable productionised solutions with security and monitoring best practices. Experienced with Cloud Security best practices. More ❯

e.g., ingesting data, cleaning, etc.). Experience with Software/Data Science Concepts: Understanding of data structures, algorithms, and common data science techniques. Experience with data science tools like Pandas, NumPy, or similar libraries for data manipulation. Experience with Cloud/Distributed Systems: Familiarity with cloud platforms (AWS, Azure, etc.) is a plus, especially if the data pipeline is running More ❯

Computer Engineering, Information Systems or a related field. Python Expertise - 6-8 years of core experience in object-oriented programming with Python, including strong proficiency in libraries such as Pandas and NumPy for data wrangling, analysis, and manipulation. Experience on Kubernetes Clusters, Dockers Containerization & Deployment, Knowledge of Apache AirFlow or Autosys scheduler tools Big Data Processing - Proven expertise in PySpark More ❯

engineering team. In this role, you will: Assist with analysis and model construction using AI and/or machine learning. Develop code in Python (XML, NetworkX, Matplotlib, Spacy, NLTK, pandas, parquet, scikit-learn, seaborn, matplotlib, NumPy). Build design concepts and detail designs. Perform development and application of NLP and ML Perform DB development including access controls to controlled access More ❯

accesses, and loading. Databases: PostgreSQL, NoSQL, Vector Databases, Graph Databases etc. ETL/ELT Concepts Data warehouse concepts SQL Competency in data exploration, analytics, and feature engineering. (Python Specific) Pandas/NumPy/Polars/PySpark Plotly/Matplotlib (some form of data visualization) Data encoding/normalizing/regularizing/etc. Understanding of Deep learning concepts and architectures like More ❯

with and a team of software engineers and must have working familiarity with one or more programming languages (our stack includes C, C++, Go/Golang, Rust, Python, numpy, pandas, and TypeScript/JavaScript) with ability to understand and describe existing customer mission systems, APIs, and performance requirements. Lead a blended team of customer operators and engineering teams to develop More ❯

Description:- Data Engineer (Python enterprise developer): 6+ years of experience in python scripting. Proficient in developing applications in Python language. Exposed to python-oriented Algorithms libraries such as NumPy, pandas, beautiful soup, Selenium, pdfplumber, Requests etc. Proficient in SQL programming, Postgres SQL. Knowledge on DevOps like CI/CD, Jenkins, Git. Experience working with AWS(S3) and Azure Databricks. Have More ❯

a quantitative emphasis in mathematics, engineering, or computer science. Minimum of 5 years of experience in Python development, with a strong understanding of object-oriented programming principles. Experience with pandas, numpy, matplotlib, scipy, and web frameworks like Flask or FastAPI is a plus. Good understanding of relational databases such as Oracle and MS SQL Server. Previous experience in front-office More ❯

Financial Systems development experience Understanding of massive parallel processing (MPP) architecture to support high volume data processing. Knowledge of Python syntax and experience with relevant libraries such as NumPy, Pandas etc. Note: If you are interested, please share your updated resume and suggest the best number & time to connect with you. If your resume is shortlisted, one of our IT More ❯

scale model deployment Design and build robust, scalable ML infrastructure, internal libraries, and reusable components that enhance team productivity Proficiency in Python and experience with ML libraries (scikit-learn, pandas, numpy) and deep learning frameworks (TensorFlow, PyTorch, Keras) Advanced hands-on experience with cloud platforms (AWS, GCP, Azure) and implementing production-grade MLOps pipelines, containerization (Docker/Kubernetes), and automated More ❯

ML libraries Experience with Docker, Kubernetes, and cloud AI platforms such as AWS Bedrock, Sagemaker, Azure ML, or GCP Vertex AI Working knowledge of data tools such as Spark, Pandas, SQL/NoSQL databases Security: TS clearance required Nice to Have Experience with LangChain, hybrid retrieval orchestration frameworks, or custom AI agent architectures Experience implementing custom authentication/authorization strategies More ❯

PyTorch, ONNX, NLTK, OpenAI, langchain, llama-index,kore.ai. DL Architectures: LLM, ANN, CNN, R-CNN, RNN, GRU, LSTM, Transformers, Attention Mechanism, Tokenisers. BERT, T5, Sentence Transformers, Foundational models. Packages: Pandas, NumPy, Spark, Matplotlib, SciPy. Cloud Technologies: AWS (EC2, S3, RDS, ECS, Lambda), Azure(VM, Functions, ACR, AKS), Digital Ocean, GCP, Paperspace. Database: MySQL, PostgreSQL, MongoDB, ChromaDB, Pinecone, SQLite. Web Frameworks More ❯

MLOps to produce analytical or visual products Knowledge of data formats such as JSON, Parquet, Avro, or CSV Ability to work with Dataframes and SQL utilizing Spark, PySpark, Python Pandas, or Polars Ability to report findings and research clearly and concisely for clients Secret clearance Bachelor's degree in a Computer Science or Computer Engineering field and 2+ years of More ❯

ML models in a financial services environment (Banking, FinTech, Insurance, or related). Technical Skills: Programming: Expert proficiency in Python (must-have) and its core data science libraries (e.g., Pandas, NumPy, Scikit-learn). Proficiency in SQL is essential. Machine Learning: Deep, hands-on experience with a wide range of ML techniques (supervised/unsupervised learning, time-series analysis, ensemble More ❯

frameworks including RAG, LangChain, TensorFlow, and PyTorch Practical experience with Generative AI and exposure to leading LLM platforms (Anthropic, Meta, Amazon , OpenAI) Proficiency with essential data science libraries including Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks Knowledge of ML-adjacent technologies, including AWS SageMaker, Kedro and MLflow. Strong skills in data preprocessing, wrangling, and augmentation techniques Experience More ❯