126 to 150 of 249 Permanent Pandas Jobs

into actionable business insights. Preferred Qualifications, Capabilities and Skills Master’s degree or background in Computer Science. Advanced proficiency in Python for data science (Pandas, NumPy, Scikit-learn, TensorFlow, Keras). Advanced experience in pattern recognition, predictive modeling, and statistical analysis. Experience with regression, classification, clustering, dimensionality reduction, and pipeline ...

5+ years of experience in Software Engineering, Test Automation, AI Engineering, or Data Engineering Strong proficiency in Python and data/AI libraries (e.g., pandas, numpy, PyTorch or similar) Solid understanding of LLMs, NLP concepts, or generative AI systems Experience with test automation frameworks (e.g., PyTest, Playwright) and CI/ ...

observability etc. Experience monitoring, maintaining, enhancing existing models over an extended time period Extensive experience with pytorch and related data science python libraries (e.g. pandas) Experience of containerising applications or models for deployment (Docker) Experience with one of the major public cloud providers (Azure, AWS, GCP) Ability to communicate technical ...

engineering, or data science Hands‐on experience with production ML systems Strong Python skills and experience with tools such as: scikit‐learn, PyTorch, TensorFlow Pandas, NumPy Hugging Face/generative AI tooling Understanding of MLOps, cloud platforms (AWS, Azure, GCP), and SQL A passion for coaching, mentoring, and developing others ...

solid understanding of machine learning and deep learning methods Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals Experience with ...

deployment or operation of forecasting, optimisation or machine learning models within a business environment. Strong Python programming skills, including experience with libraries such as pandas and scikit‐learn. Strong experience deploying, monitoring and maintaining machine learning or analytical solutions in production environments, including automated testing, model monitoring and version control. ...

with significant industry or research experience in the field Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals Experience with ...

Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) < Strong knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib) Strong software development skills (Python is the preferred language) Proven experience in deploying ML/AI services suing Kubernetes & KubeFlow Strong management ...

statistics Solid foundation on data structures and algorithms Proficiency in Python for numerical/statistical programming (our group relies heavily on Numpy/Pandas/Scikit-learn) Ability to interpret and write complex SQL queries### Experiencewith big data technologies, such as Hive and Spark Track record of leading the deployment ...

need everything) Experience of working in an Agile delivery team Strong analytic skills related to working with unstructured datasets Python (PySpark, Pandas, PyArrow) Distributed data processing (Apache Spark) Data ETL (Apache Airflow, AWS Step Functions, Apache NiFi) Cloud services (AWS, Azure or GCP) Messaging/Streaming (Kafka, AWS SQS, Other ...

5+ years in applied data science, with significant experience on commercial problems (churn, LTV, propensity, attribution, pricing, or similar).* Strong SQL and Python (pandas, scikit-learn, statsmodels). Comfortable building production-grade code, not just notebooks.* Hands-on experience with Snowflake (or a comparable cloud data warehouse — BigQuery, Redshift ...

need everything) Experience of working in an Agile delivery team Strong analytic skills related to working with unstructured datasets Python (PySpark, Pandas, PyArrow) Distributed data processing (Apache Spark) Data ETL (Apache Airflow, AWS Step Functions, Apache NiFi) Cloud services (AWS, Azure or GCP) Messaging/Streaming (Kafka, AWS SQS, Other ...

vulnerability remediation, audit evidence, regulatory controls, and secure operations. Oracle/SQL or comparable query skills for extraction, transformation, analysis, and reporting. Experience with Pandas, NumPy, Matplotlib, and Seaborn preferred. Bachelor's or master's degree in Computer Science, Information Systems, Engineering, Data Science, Statistics, Design, or related field ...

need everything) Experience of working in an Agile delivery team Strong analytic skills related to working with unstructured datasets Python (PySpark, Pandas, PyArrow) Distributed data processing (Apache Spark) Data ETL (Apache Airflow, AWS Step Functions, Apache NiFi) Cloud services (AWS, Azure or GCP) Messaging/Streaming (Kafka, AWS SQS, Other ...

async Python frameworks) Strong working knowledge of modern machine learning — able to understand, integrate, and extend the functionality of an ML library (NumPy, SciPy, Pandas, and frameworks such as scikit-learn or PyTorch) Understanding of core ML concepts — model training, evaluation, and production trade-offs — enough to design robust interfaces ...

building production systems that deliver measurable business impact Technical Mastery: High proficiency in Python and SQL. Expert-level experience with the Python data stack (pandas, NumPy, scikit-learn) and at least one major ML framework (such as PyTorch or XGBoost/LightGBM) Systemic Problem Solving: Ability to work on unique ...

transformation methodologies Experience contributing to large-scale, efficient and performant analytics workflows, including ETL, orchestration, and distributed compute, using industry-standard libraries such as Pandas, Polars, and Dask. Experience working in a modern software engineering environment leveraging Agile (Scrum), DevSecOps methodologies, CI/CD workflows, and tools including ...

mathematics, epidemiology or a closely related field . Essential Application Demonstrable programming skills in Python, including common data science/machine learning libraries (eg pandas, scikit-learn or PyTorch/JAX). Essential Application/interview Working knowledge of core machine learning methods (eg regression, classification, clustering). Essential Application ...

team, presenting results with their uncertainty and QC so they can understand and check them themselves. Fluency in Python and its scientific stack, including pandas, NumPy and SciPy, and in working with coding agents. SQL and relational schema design for samples, plates and results. Turning scientists’ questions into requirements ...

deploy Machine Learning capabilities and techniques into other systems. Familiarity with the Python data science stack through exposure to libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit‐learn Take pride in writing clean, reusable, maintainable and well‐tested code A desire to learn and embrace new and emerging ...

lifecycle in production Communicate insights to executive stakeholders with clarity What you bring 4+ years applied data science with production deployments Strong Python (pandas, scikit-learn, PyTorch) and SQL Solid grounding in statistics, experimentation and causal inference Experience with at least one MLOps stack (MLflow, SageMaker, Vertex) Nice to have ...

quality, integrity, and dashboard performance issues Act as a trusted advisor to client stakeholders on data analytics matters Python for data analysis and automation (pandas, numpy, scipy, etc.) Data Engineering Knowledge: Familiarity with ETL processes, data integration tools, and modern data platforms (e.g., Databricks) Communication: Excellent stakeholder management and presentation ...

performance optimisation Networking Nice to have: Data engineering experience in Python, e.g. with libraries like Dagster, Prefect etc Experience optimising dataframe code, e.g. in Pandas or ideally Polars Experience of machine learning techniques and related libraries and frameworks e.g. scikit-learn, Pytorch, Tensorflow etc Experience in scientific computing with other ...

technologies is highly desirable, including PostgreSQL, MongoDB, and vector databases such as Qdrant, Milvus or pgvector. Experience with Python data-processing libraries such as Pandas or Polars is highly desirable. Nice to Have Experience working on AI or machine learning platforms. Familiarity with stream processing and event-driven architectures. Experience ...

market data symbology, with an interest in developing further expertise in these areas Proficiency with SQL and Python for exploratory data analysis (PySpark, pandas, Jupyter Notebooks) Ability to document and clearly explain complex data analysis findings Exceptional attention to detail and effective communication skills Ability to think both independently ...