Essential Skills and Experience: Proven ability to solve complex, real-world problems through data science and analytics. Experience coaching and reviewing work of junior team members. Strong Python skills (pandas, numpy, scikit-learn) and a solid grounding in probability and statistics. Deep knowledge of machine learning methods and their practical application. Experience managing multiple end-to-end data science projects More ❯
validation techniques such as cross-validation, bootstrapping, and assessing the statistical significance of model improvements. Excellent knowledge of data analysis, visualization, and preprocessing techniques. Familiarity with tools such as Pandas, NumPy, and Matplotlib. Experience deploying Classical and Modern Time Series Forecasting solutions using tools such as Neural Prophet, SARIMA, Chronos, etc Familiar with cloud-based machine learning platforms such as More ❯
Two to four years of experience in data science or machine learning with demonstrable expertise in geospatial analysis. Strong proficiency in Python with experience in scientific computing libraries (NumPy, Pandas, Scikit-learn, SciPy). Hands-on experience with geospatial Python libraries such as GDAL, GeoPandas, Shapely, Rasterio, Folium, or similar. Solid understanding of machine learning algorithms, statistical modeling, and time More ❯
the adoption of best practices in data science across the organisation, lead other data science engineers MINIMUM QUALIFICATIONS Industry experience using Python for data science (e.g. numpy, scipy, scikit, pandas, etc.) and SQL or other languages for relational databases. Experience with a cloud platform such as (AWS, GCP, Azure etc.) Experience with common data science tools; statistical analysis, mathematical modelling More ❯
with experience building complex, maintainable systems Professional software development experience with a track record of delivering high-quality, production-grade code Experience with scientific computing libraries such as NumPy, Pandas, or SciPy in production environments Holistic software development mindset covering testing, documentation, security, and performance Track record of mentoring other engineers and sharing knowledge across teams Working knowledge of mathematical More ❯
a related field. Proficient in object-oriented programming, especially Python, with a minimum of 6-8 years of core python development experience. Strong competency with Python libraries such as Pandas and NumPy for data wrangling, analysis, and manipulation. Expertise in PySpark for large-scale data processing and loading into databases. Proficiency in data querying and manipulation with Oracle and PostgreSQL. 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 ❯
Tech Stack The tech stack for the service-oriented architecture includes: Django Erlang REST Framework PostgreSQL PostGIS AWS ES6 React.js Alt.js Node.js Express Amazon Redshift Kubernetes Docker Redis Celery Pandas Numpy Scrapy Git with Zenhub Jenkins Elasticsearch Python Developer Position Python Developer Times Fastest Growing Fintech Quant Capital is urgently looking for a Python developer to join our high-profile More ❯
Ashburn, Virginia, United States Hybrid / WFH Options
Adaptive Solutions, LLC
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 ❯
Requirements 2-4 years' experience in applied machine learning and generative AI, including work with large language models. Strong Python programming skills with experience in core ML libraries (numpy, pandas, scikit-learn, boosting methods). Proven ability to design, test, and deploy production-ready machine learning solutions. Hands-on experience in data processing and feature engineering for complex datasets. Solid More ❯
Requirements 2-4 years' experience in applied machine learning and generative AI, including work with large language models. Strong Python programming skills with experience in core ML libraries (numpy, pandas, scikit-learn, boosting methods). Proven ability to design, test, and deploy production-ready machine learning solutions. Hands-on experience in data processing and feature engineering for complex datasets. Solid 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 ❯
Edinburgh, Midlothian, Scotland, United Kingdom Hybrid / WFH Options
McGregor Boyall
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 ❯
Python, PySpark, or other object-oriented development languages Required Skills: 1) Min 5 years of solid Pentaho-specific ETL development experience 2) Min 2 years of Python and PySpark (Pandas are ok, if the developer is very strong otherwise) 3) 3 or more years of development within the CIA or NSA environment. Desired Skills: 3a) Pentaho customized components expertise using More ❯
closely with global colleagues; communicate designs clearly. Requirements AWS data stack, hands on experience: Glue, Airflow/MWAA, Athena, Redshift, RDS, S3. Strong coding skills in Python & PySpark/Pandas & SQL. CI/CD automation: AWS CodePipeline, CloudFormation (infrastructure as code). Architect-level experience: At least 5 years in a senior/lead role. Security-first mindset: Solid understanding More ❯
a commercial data analysis role 📊 Strong technical skills in SQL Strong dashboard and data viz skills in PowerBI and DAX Strong statistical analytics experience in Python and associated libraries PANDAS, NumPy, SciPy etc. 🐍 Automate when you should with Power Platform and other tools Experience engaging with stakeholders 🗣️ Ability to interrogate data, find trends, anomalies and leverage this data to make More ❯
Microsoft Technologies: Proficiency with Azure services, Microsoft Graph API, andexperience integrating Python applications with Azure for access control reviews and reporting.Reporting and Visualization: Experience using reporting libraries in Python (Pandas, Matplotlib,Plotly, Dash) to build dashboards and reports related to security and access control (link removed)munication Skills: Ability to collaborate with various stakeholders, explain complextechnical solutions, and deliver high More ❯
closely with global colleagues; communicate designs clearly. Requirements AWS data stack, hands on experience: Glue, Airflow/MWAA, Athena, Redshift, RDS, S3. Strong coding skills in Python & PySpark/Pandas & SQL. CI/CD automation: AWS CodePipeline, CloudFormation (infrastructure as code). Architect-level experience: At least 5 years in a senior/lead role. Security-first mindset: Solid understanding More ❯
scalable workflows. Help grow and shape the data science team and its role within the wider business. What We’re Looking For Strong technical foundation with proficiency in Python (Pandas, NumPy, Scikit-learn), SQL, and cloud platforms (GCP or AWS). Experience with modern data warehouses (BigQuery, Snowflake, Redshift). Proven experience in deploying machine learning models or optimisation algorithms More ❯
s or Master’s degree in a STEM field: Statistics, Mathematics, Computer Science, Engineering, or similar. Programming proficiency: Strong experience with Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation More ❯
s or Master’s degree in a STEM field: Statistics, Mathematics, Computer Science, Engineering, or similar. Programming proficiency: Strong experience with Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation More ❯
s or Master’s degree in a STEM field: Statistics, Mathematics, Computer Science, Engineering, or similar. Programming proficiency: Strong experience with Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation 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 ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Salt Search
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 ❯
