1 to 25 of 65 Remote Permanent Pandas Jobs

rapid MVP development and iteration. Data Storyteller makes technical findings accessible and impactful. Connector collaborates seamlessly across data, commercial, and ops teams. Hard Skills Required Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) essential; R (desirable) Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP Machine Learning & AI: Classification More ❯

or related field (or equivalent experience) 3-5 years of experience in data engineering (healthcare/medical devices preferred but not required) Strong Python programming and data engineering skills (Pandas, PySpark, Dask) Proficiency with databases (SQL/NoSQL), ETL processes, and modern data frameworks (Apache Spark, Airflow, Kafka) Solid experience with cloud platforms (AWS, GCP, or Azure) and CI/ More ❯

managers, and async/await patterns - Data structures and algorithms for efficient data processing and model optimization - Error handling and debugging using try-catch blocks, logging, and debugging tools - Pandas and NumPy for data manipulation, cleaning, and numerical operations - SQLAlchemy or psycopg2 for database connectivity and ORM operations - Boto3 for AWS service integration and automation - Lambda function development with proper More ❯

managers, and async/await patterns - Data structures and algorithms for efficient data processing and model optimization - Error handling and debugging using try-catch blocks, logging, and debugging tools - Pandas and NumPy for data manipulation, cleaning, and numerical operations - SQLAlchemy or psycopg2 for database connectivity and ORM operations - Boto3 for AWS service integration and automation - Lambda function development with proper More ❯

managers, and async/await patterns - Data structures and algorithms for efficient data processing and model optimization - Error handling and debugging using try-catch blocks, logging, and debugging tools - Pandas and NumPy for data manipulation, cleaning, and numerical operations - SQLAlchemy or psycopg2 for database connectivity and ORM operations - Boto3 for AWS service integration and automation - Lambda function development with proper More ❯

systems Background of working in hedge fund or alternative investment environment, working directly with investment team on tech delivery Strong understanding of Python, with libraries/frameworks such as Pandas, NumPy, and PySpark Strong understanding of distributed computing, with experience using frameworks like Databricks Strong experience with Azure or other cloud platforms (AWS) Strong experience building data pipelines or ETL More ❯

workstreams to elevate team capability. Essential Skills & Experience Proven experience in analytics engineering , data engineering , or model development roles. Advanced proficiency in Python (including libraries such as NumPy and Pandas) and SQL . Demonstrated ability to deliver production-ready solutions in a commercial environment. Strong communication skills with the ability to engage stakeholders and translate technical work into business outcomes. More ❯

workstreams to elevate team capability. Essential Skills & Experience Proven experience in analytics engineering , data engineering , or model development roles. Advanced proficiency in Python (including libraries such as NumPy and Pandas) and SQL . Demonstrated ability to deliver production-ready solutions in a commercial environment. Strong communication skills with the ability to engage stakeholders and translate technical work into business outcomes. More ❯

sorting, data filtering, pivot tables, vlookup, SUMIF/SUMIFS, charts. BI tools. Desirable PowerBI A/B testing. Split principles, test planning, logging. Desirable hard skills Python. Data analysis, pandas, numpy, scipy, statsmodels, seaborn, matplotlib etc. ETL processes. Airflow, Pentaho etc. IT understanding. Client-server processes. API. Back-end and front-end. Parsing. Algorithms and data structures. Management. Sprints, AGILE. More ❯

sorting, data filtering, pivot tables, vlookup, SUMIF/SUMIFS, charts. BI tools. Desirable PowerBI A/B testing. Split principles, test planning, logging. Desirable hard skills Python. Data analysis, pandas, numpy, scipy, statsmodels, seaborn, matplotlib etc. ETL processes. Airflow, Pentaho etc. IT understanding. Client-server processes. API. Back-end and front-end. Parsing. Algorithms and data structures. Management. Sprints, AGILE. More ❯

Monitoring & Alerting: Prometheus, Datadog, Pagerduty Telemetry Standards: OpenTelemetry Application & Data Ecosystem (Supporting): Application Languages/Frameworks: Python, FastAPI, Flask, Node.js, React Data Streaming: Apache Kafka Data Processing/Transformation: Pandas, DBT Workflow Orchestration: Apache Airflow, Ray Machine Learning Stack: Serving: Triton Inference Server MLOps/Experiment Tracking: Weights and Biases, DVC Libraries/Frameworks: Transformers, HuggingFace Model Optimization/Formats More ❯

3+ years in AI, machine learning, or data science roles. Proven track record of deploying AI models into production environments. Experience with data manipulation and analysis, using tools like Pandas and SQL. Involvement in full project lifecycles, from concept to deployment and monitoring. Ability to work in fast-paced, agile settings and adapt to changing project requirements. With Myn, you More ❯

Object Detection, LLMs, and frameworks such as Transformers (Hugging Face), PyTorch, OpenCV, YOLO. Programming: Strong Python (3.9+) skills, including OOP, async patterns, data structures, debugging. Data Processing: Proficient with Pandas, NumPy, SQLAlchemy/psycopg2, AWS Boto3. Cloud & Infrastructure: Hands-on AWS (Lambda, S3, CloudWatch, IAM, CDK, SQS, EKS/ECS/Kubernetes). API Development: FastAPI, REST API design, external More ❯

in designing and implementing efficient data pipelines, including performance tuning and optimization. Proven ability to apply machine learning techniques to real-world problems. Familiarity with core libraries such as Pandas, NumPy, Scikit-learn, SciPy, and Polars is expected. Experience with digital signal processing, mobile sensor physics, or behavioural signal design. Proven track record of designing and delivering scalable data products More ❯

Familiarity with data pipeline orchestration and a strong grasp of DevSecOps best practices in cloud-native environments • Hands-on experience with key tools and frameworks, including: o Python, NumPy, Pandas, scikit-learn o TensorFlow or PyTorch o Elasticsearch, Logstash, Kibana • Preferred Experience in GDS (Government Digital Services) or USDS (U.S. Digital Services) Education Requirement • Shall have at a minimum, a More ❯

with external systems. Deploy scalable AI systems using AWS (Lambda, S3, SQS, EKS/ECS), CDK , and modern DevOps practices. Collaborate on infrastructure and data pipelines using SQLAlchemy, Boto3, Pandas, and Airflow . Contribute to real-time AI services , model versioning, and advanced fine-tuning (LoRA, QLoRA, etc.). Qualifications Solid Python skills (3.9+) with deep knowledge of async, OOP More ❯

Required Skills & Experience: Bachelor's degree in Computer Science, Mathematics, Statistics, Business Administration or related field Advanced knowledge of SQL Good knowledge of Python, including popular Data Science packages (pandas, matplotlib, seaborn, numpy, sklearn) Familiarity with what is happening under the hood of popular Machine Learning algorithms Strong problem-solving skills and attention to detail Strong communication and collaboration skills More ❯

recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

recently completed Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

skills. Bonus skills • Experience deploying and managing applications with Azure and Docker. • Familiarity with frameworks like LangChain and Retrieval-Augmented Generation (RAG) models for AI-driven applications. • Experience with pandas for data manipulation. What’s on offer • Regular salary reviews recognising performance and contribution. • Generous annual leave: 25 days plus three days over Christmas. • Flexible hybrid working to support work More ❯

learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from More ❯

or similar domains with forecasting needs. Skills and competencies Essential: Experience working with Python or R in a production or research setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational More ❯