1 to 25 of 75 Remote 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 ❯

of solving problems that spreadsheets can't touch. What you'll do Engineer and analyse large datasets to deliver insights that shape client strategy. Build scalable solutions with Python (Pandas/NumPy), SQL, and cloud tools like BigQuery on GCP . Support senior business experts by turning raw financial data into decisions that matter. Design and run data mapping projects More ❯

frameworks like Hugging Face Transformers , PyTorch , YOLO , OpenCV , and Pillow Designing and deploying AI services via FastAPI , AWS Lambda , EKS/ECS , and S3 Creating scalable data pipelines with Pandas , NumPy , SQLAlchemy , and Airflow Supporting real-time model inference, edge deployments, and API integrations Working closely with a technical lead in a service-based and serverless architecture Essential Python Engineer 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 ❯

Services - Mandatory Good understanding of quantitative finance Good experience developing and optimising Python-based calculators and models. Strong experience developing high-performance APIs using Flask or FastAPI. Expertise in Pandas, NumPy and other computing libraries. Strong experience liaising with front-office stakeholders What you'll get in return Initial 6-month contract with extensions Up to £700pd umbrella London-based More ❯

Services - Mandatory Good understanding of quantitative finance Good experience developing and optimising Python-based calculators and models. Strong experience developing high-performance APIs using Flask or FastAPI. Expertise in Pandas, NumPy and other computing libraries. Strong experience liaising with front-office stakeholders What you'll get in return Initial 6-month contract with extensions Up to £700pd umbrella London-based More ❯

Services - Mandatory Good understanding of quantitative finance Good experience developing and optimising Python-based calculators and models. Strong experience developing high-performance APIs using Flask or FastAPI. Expertise in Pandas, NumPy and other computing libraries. Strong experience liaising with front-office stakeholders What you'll get in return Initial 6-month contract with extensions Up to £700pd umbrella London-based 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 ❯

reliability and accuracy. Stay up-to-date with the latest ML research and tools. Required Skills & Experience Strong proficiency in Python and its ML/data libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow or PyTorch). Hands-on experience with Amazon SageMaker , including training, tuning, and deploying models. Solid understanding of machine learning algorithms and statistical methods. Experience with cloud 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 ❯

Databases & Analytics: Snowflake, PostgreSQL, MongoDB, DataStax/Astra DB, Data modeling, ETL * Cloud & DevOps: AWS (S3, SageMaker), * Tools & Frameworks: Git, Jira, Confluence, PyCharm, Notebooks * Machine Learning and Deep Learning: Pandas, NumPy, Scikit-Learn, OpenCV, PyTorch, Tensorflow, OpenCV * GenAI/LLMs: Hands-on experience with generative AI tools and frameworks Geospatial Tools: Experience with GIS platforms such as ArcGIS, QGIS, CARTO 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 ❯

up-to-date with emerging trends and technologies in the field of data science. Requirements Proven experience as a data scientist using Python and a range of libraries (Numpy, Pandas, Scikit-Learn, Matplotlib, Plotly etc.). Strong expertise in statistical modelling, machine learning, and data mining techniques. Experience in computer vision is essential. Data engineering (pipelines, databases, infrastructure), ideally with 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.). AI Engineer requirements: Solid Python skills (3.9+) with deep knowledge of More ❯

AI requirements into scalable solutions. Essential Experience & Skills 5+ years' engineering experience, with at least 3 years in ML Ops, Data Engineering, or AI infrastructure. Strong Python engineering skills (Pandas, Numpy, Jupyter, FastAPI, SQLAlchemy). Expertise in AWS services (certification desirable). Proven experience deploying and supporting LLMs in production. Strong understanding of LLM fine-tuning (PyTorch, TensorFlow, Hugging Face More ❯