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 ❯
Experience in both data engineering and machine learning, with a strong portfolio of relevant projects. Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or Kafka. Strong understanding of SQL, NoSQL, and data modeling. Familiarity with More ❯
Experience in both data engineering and machine learning, with a strong portfolio of relevant projects. Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or Kafka. Strong understanding of SQL, NoSQL, and data modeling. Familiarity with 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 ❯
features end-to-end, from ideation to deployment. Be on-call for urgent AI model fixes or system failures. Qualifications Proficiency in Python and related libraries (e.g., NumPy, SciPy, pandas) is required. Strong production experience with at least one framework: LangChain, AutoGen, or CrewAI. Deep understanding of agentic systems, autonomous workflows, and LLM-based automation. Experience deploying and fine-tuning 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 Desirable: Working knowledge of More ❯
or data engineering. Ability to work standard European time-zone hours and legal authorisation to work in your country of residence. Strong experience with Python’s data ecosystem (e.g., Pandas, NumPy) and deep expertise in SQL for building robust data extraction, transformation, and analysis pipelines. Hands-on experience with big data processing frameworks such as Apache Spark, Databricks, or Snowflake More ❯
or data engineering. Ability to work standard European time-zone hours and legal authorisation to work in your country of residence. Strong experience with Python’s data ecosystem (e.g., Pandas, NumPy) and deep expertise in SQL for building robust data extraction, transformation, and analysis pipelines. Hands-on experience with big data processing frameworks such as Apache Spark, Databricks, or Snowflake More ❯
/or other relevant languages (e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for AI model deployment. Data Visualisation: Ability to More ❯
model performance evaluation, hyperparameter tuning, and maintenance using tools like Vertex AI Pipelines. Cloud Computing (Google Cloud Platform - GCP Preferred) Technical Expertise & Tools Python: Advanced proficiency in data analysis (Pandas, NumPy), machine learning, PI development (Flask/FastAPI), and writing clean, maintainable code. SQL: Expertise in querying, database design/optimization, stored procedures, functions, partitioning/clustering strategies for BigQuery More ❯
customer experience principles and marketing analytics including customer journey mapping, conversion optimization, and marketing funnel analysis Proficiency in Python with extensive experience in data science & AI libraries (e.g.scikit-learn, pandas, NumPy, SciPy, etc) Experience with ML frameworks such as TensorFlow, PyTorch, XGBoost, LightGBM, or similar Strong SQL skills and experience with data warehousing solutions (Snowflake, BigQuery, Redshift) Experience with cloud More ❯
Requirements for Success Here are the key qualifications and experiences you'll need to succeed in this role: Proven Software Developer in Test Experience You should have a proven track record as a Software Developer in Test. Extensive Automation Testing More ❯
track drift, response quality and spend; implement automated retraining triggers. Collaboration - work with Data Engineering, Product and Ops teams to translate business constraints into mathematical formulations. Tech stack Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow) SQL (Redshift, Snowflake or similar) AWS SageMaker → Azure ML migration, with Docker, Git, Terraform, Airflow/ADF Optional extras: Spark, Databricks, Kubernetes. What you … yrs optimisation/recommender work at production scale (dynamic pricing, yield, marketplace matching). Mathematical optimisation know-how - LP/MIP, heuristics, constraint tuning, objective-function design. Python toolbox: pandas, NumPy, scikit-learn, PyTorch/TensorFlow; clean, tested code. Cloud ML: hands-on with AWS SageMaker plus exposure to Azure ML; Docker, Git, CI/CD, Terraform. SQL mastery for More ❯
approaches. Deployment: ship a model as a container, update an Airflow (or Azure Data Factory) job. Review: inspect dashboards, compare control vs. treatment, plan next experiment. Tech stack Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow) SQL (Redshift, Snowflake or similar) AWS SageMaker → Azure ML migration, with Docker, Git, Terraform, Airflow/ADF Optional extras: Spark, Databricks, Kubernetes. What you … yrs optimisation/recommender work at production scale (dynamic pricing, yield, marketplace matching). Mathematical optimisation know-how - LP/MIP, heuristics, constraint tuning, objective-function design. Python toolbox: pandas, NumPy, scikit-learn, PyTorch/TensorFlow; clean, tested code. Cloud ML: hands-on with AWS SageMaker plus exposure to Azure ML; Docker, Git, CI/CD, Terraform. SQL mastery for More ❯
approaches. Deployment: ship a model as a container, update an Airflow (or Azure Data Factory) job. Review: inspect dashboards, compare control vs. treatment, plan next experiment. Tech stack Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow) SQL (Redshift, Snowflake or similar) AWS SageMaker → Azure ML migration, with Docker, Git, Terraform, Airflow/ADF Optional extras: Spark, Databricks, Kubernetes. What you … yrs optimisation/recommender work at production scale (dynamic pricing, yield, marketplace matching). Mathematical optimisation know-how - LP/MIP, heuristics, constraint tuning, objective-function design. Python toolbox: pandas, NumPy, scikit-learn, PyTorch/TensorFlow; clean, tested code. Cloud ML: hands-on with AWS SageMaker plus exposure to Azure ML; Docker, Git, CI/CD, Terraform. SQL mastery for More ❯
Designing Generative AI Proof of Concept. Contribute to AI infrastructure Building reliable, scalable, and flexible systems. Influence Opinion and decision-making across AI and ML Skills Python SQL/Pandas/Snowflake/Elasticsearch Docker/Kubernetes Airflow/Spark Familiarity with GenAI models/libraries Requirements 4+ years of relevant software engineering experience post-graduation A degree (ideally a More ❯
Designing Generative AI Proof of Concept. Contribute to AI infrastructure Building reliable, scalable, and flexible systems. Influence Opinion and decision-making across AI and ML Skills Python SQL/Pandas/Snowflake/Elasticsearch Docker/Kubernetes Airflow/Spark Familiarity with GenAI models/libraries Requirements 4+ years of relevant software engineering experience post-graduation A degree (ideally a More ❯
Designing Generative AI Proof of Concept. Contribute to AI infrastructure Building reliable, scalable, and flexible systems. Influence Opinion and decision-making across AI and ML Skills Python SQL/Pandas/Snowflake/Elasticsearch Docker/Kubernetes Airflow/Spark Familiarity with GenAI models/libraries Requirements 4+ years of relevant software engineering experience post-graduation A degree (ideally a More ❯
and a desire to understand complex issues Beneficial experience • Experience in trading or execution roles • Experience with equity/credit markets • Research using large, messy datasets • Familiarity with Linux • Pandas Benefits: Working alongside other extremely talented and driven engineers Extremely lucrative salary, bonus and benefits More ❯
is looking for a Data Scientist to join its innovative team. This role requires hands-on experience with machine learning techniques and proficiency in data manipulation libraries such as Pandas, Spark, and SQL. As a Data Scientist at PwC, you will work on cutting-edge projects, using data to drive strategic insights and business decisions. If you have strong analytical … development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we use Azure/GCP/AWS). Skills we'd also like to hear about: Evidence of modelling experience applied More ❯
is looking for a Data Scientist to join its innovative team. This role requires hands-on experience with machine learning techniques and proficiency in data manipulation libraries such as Pandas, Spark, and SQL. As a Data Scientist at PwC, you will work on cutting-edge projects, using data to drive strategic insights and business decisions. If you have strong analytical … development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we use Azure/GCP/AWS). Skills we'd also like to hear about: Evidence of modelling experience applied More ❯
is looking for a Data Scientist to join its innovative team. This role requires hands-on experience with machine learning techniques and proficiency in data manipulation libraries such as Pandas, Spark, and SQL. As a Data Scientist at PwC, you will work on cutting-edge projects, using data to drive strategic insights and business decisions. If you have strong analytical … development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we use Azure/GCP/AWS). Skills we'd also like to hear about: Evidence of modelling experience applied More ❯
is looking for a Data Scientist to join its innovative team. This role requires hands-on experience with machine learning techniques and proficiency in data manipulation libraries such as Pandas, Spark, and SQL. As a Data Scientist at PwC, you will work on cutting-edge projects, using data to drive strategic insights and business decisions. If you have strong analytical … development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow). Understanding of machine learning techniques. Experience with data manipulation libraries (e.g. Pandas, Spark, SQL). Git for version control. Cloud experience (we use Azure/GCP/AWS). Skills we'd also like to hear about: Evidence of modelling experience applied More ❯
the design and development of advanced AI and machine learning models, integrating plasma physics insights to innovate semiconductor solutions, such as plasma etch and deposition. Utilize Python libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) to architect and prototype cutting-edge ML systems, leveraging Linux environments. Able to expand programming expertise to other languages such as C++ and Java. Drive … testing, and experience leading mid-scale development projects. Advanced proficiency in at least one of Python, C++, Fortran, Julia, or Java, with experience in AI/ML libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) and familiarity with Linux environments. Strong understanding of physics and engineering principles, ideally with plasma physics knowledge relevant to semiconductor processing. Exceptional communication and leadership More ❯
suits someone who is not only technically strong, but solution-oriented, strategically minded, and able to communicate insights clearly to both technical and non-technical audiences. Requirements: Advance Python (Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch) & SQL skills. (Snowflake a plus) Experience with Data warehousing and database technologies Solid machine learning experience (modelling to deployment) Cloud exposure (GCP/AWS More ❯
