- FR
Intermediate Data Scientist
Intermediate Data Scientist
About the role
Intermediate Data Scientist
As a Data Scientist, you will be responsible for participating in development, training, deployment and management of data quality monitoring models using ML and GenAI. The person should be an experienced data scientist and shall also have the mindset to keep improvement of the model development process. You will work autonomously and follow a continuous improvement approach, ensuring a high-quality code that adheres to our design, norms, and standards. You will be accountable for delivering solutions that meet both functional and non-functional requirements, taking into account the principles of Agile development.
Capital Markets IT involves technological solutions and systems used in financial markets for trading, investment, and related activities. This includes electronic trading platforms, risk management systems, market risk, counterparty risk, algorithmic trading, data analytics, and Regulatory measures. The use of advanced technologies like API's, artificial intelligence and cloud solutions are also becoming increasingly prevalent in capital markets to enhance efficiency and decision-making processes.
Job Responsibilities :
- Identify and create relevant features from transaction data to improve model performance.
- Perform feature selection and dimensionality reduction to enhance model efficiency.
- Develop, train, and evaluate machine learning models using transaction data.
- Implement cross-validation and hyperparameter tuning to optimize model performance.
- Monitor model performance over time to detect and address issues such as data drift and model degradation.
- Implement model retraining and updating processes to maintain model accuracy and relevance.
- Develop and execute strategies to integrate Generative AI tools and techniques into transaction data monitoring processes, improving efficiency and reducing development time.
- Design tests and refining prompts for LLM to improve accuracy, reliability and efficiency.
- Identify opportunities to augment data science workflows using GenAI, enhancing model development, data analysis, and feature engineering capabilities.
- Collaborate with data engineers, software developers, and business analysts to ensure seamless integration of data quality monitoring processes.
- Work closely with domain experts to understand transaction data requirements and business rules.
- Effectively communicate data quality findings, model performance, and project progress to stakeholders.
- Provide actionable insights and recommendations to improve data quality and model performance.
- Maintain comprehensive documentation of data quality monitoring processes, machine learning models, and generative AI models and processes.
- Document data preprocessing steps, feature engineering techniques, and model evaluation results.
- Stay updated with the latest advancements in machine learning, generative AI, and data quality monitoring techniques.
- Experiment with new tools, technologies, and methodologies to enhance data quality monitoring and model performance.
Your profile
Job Requirements:
- Candidates should have a minimum of 6 years' experience in relevant activities
- At least Bachelor's Degree in Computer Science, Information Technology, Programming & Systems Analysis, Science (Computer Studies) or related fields.
- Proficiency in languages such as Python, R, SQL, and Java or Scala.
- Strong understanding of statistical methods and concepts.
- Experience with data manipulation libraries (e.g., pandas, dplyr) and data analysis tools.
- Knowledge of machine learning algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
- Expertise in analyzing and forecasting time series data.
- Ability to create visualizations using tools like Matplotlib, Seaborn, ggplot2, or Tableau.
- Big Data Technologies: Familiarity with big data tools such as Hadoop, Spark, and distributed computing.
- Database Management: Experience with relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra).
- Docker/Kubernetes, Kafka, Spark, Mongo DB
- Data Wrangling: Skills in cleaning, transforming, and preparing data for analysis.
- Knowledge on implementing ML and GenAI solutions AWS (Bedrock, SageMaker etc.)
- Experience in supporting capital market applications and trading systems, ideally within the dynamic landscape of Market Risk/Front Office operations with a commendable grasp of financial products (Treasury, FX, Credit, IRD, Bonds, RSF etc.).
- Experience in Business intelligence tools
- Experience in working with application monitoring and automation
- Experience in Banking environment, especially in Capital Market IT
About Antaes
Founded in 2007, Antaes is a Swiss management and technology consulting company ranked among the top 15 consulting firms in Switzerland. We employ over 300 experienced consultants who share our passion.
With offices in Switzerland, Singapore, Hong Kong and France, we support our Swiss and international customers at clients in the following areas:
- Organization and transformation consulting
- Industrial Engineering
- Information Systems Management
By joining our teams you will discover :
- A dynamic team in a start-up spirit
- Human support and career development monitoring
- Challenges to help develop your network
- Events: team building, meet-up, workshop, Winter Event ...
-
An @HappyAtWork certified company with a committed CSR policy (Ecovadis2023 Gold Medal)
Engineering Project Coordinator
To join our Life Sciences team in Vaud, we are looking for an Engineering Project Coordinator in the pharmaceutical sector.
The project:
- Act as the central point in the project coordination,
- Facilitate and manage the "project cockpit" activities,
- Liaise with project leads and core teams,
- Follow > anticipate > expedite > escalate,
- Consolidate documentation to deliver an integrated project reporting system
In charge of the key "project coordination" activities :
Collect data - prepare reporting and correspondence
- Centralizing - orchestrating flow of information,
- Keeping key indicators and registers up to date,
- Ensure visibility short term activities,
Control / monitoring / expediting
- Preparing / anticipating,
- Hunting due / overdue actions,
- Ensure the scheduling follow-up of the critical due actions,
- Prepare key project meeting and MoM for follow-up,
- Owns the short term activities tracking log,
- Facilitating timely resolutions of critical issues.
Biotech Process Expert
- You will be involved in the production of biological/biotechnological products
- You will also be responsible for the preparation and processing and GMP-compliant documentation of production processes, as well as assisting in the processing of deviations, change procedures and CAPAs.
- You will also be responsible for other tasks such as:
- Maintaining GMP status for devices (e.g. maintenance, calibration, qualification)
- Collaboration in cross-site teams on internal and external projects
- Creation and review of documents such as work instructions and reports
Electrical project manager
- Carry out and monitor new build and renovation projects in various building sectors.
- Draw up pre-projects, specifications, calls for tender and acceptance procedures in collaboration with operators.
- Ensure correct sizing of electrical installations.
- Administrative follow-up (planning, budget, reporting).
- Support external offices and monitor internal and external service providers.
Automation Engineer
- Analyze needs and risks,
- Define specifications, URS, strategy and design,
- Maintaining relationships with suppliers,
- Manage production, FAT/SAT follow-up, qualification and validation, right through to commissioning,
- Check programming, documentation, etc.
- Driving improvements and corrective maintenance.
Industrial Electrical Draughtsman - Designer
- Follow-up of electrical drawing requests (in-house or via service providers).
- Create/update electrical diagrams with SEE Electrical Expert.
- Drawing schematics/pneumatic diagrams with AutoCAD.
- Updating of infrastructure, safety and fire plans.
- Environment and component management in SEE Electrical Expert.
- Rigorous archiving of documents according to internal standards.
- Work in liaison with project and maintenance teams.
- Drafting of specifications for subcontractors.
Intermediate Data Scientist
About the role
Intermediate Data Scientist
As a Data Scientist, you will be responsible for participating in development, training, deployment and management of data quality monitoring models using ML and GenAI. The person should be an experienced data scientist and shall also have the mindset to keep improvement of the model development process. You will work autonomously and follow a continuous improvement approach, ensuring a high-quality code that adheres to our design, norms, and standards. You will be accountable for delivering solutions that meet both functional and non-functional requirements, taking into account the principles of Agile development.
Capital Markets IT involves technological solutions and systems used in financial markets for trading, investment, and related activities. This includes electronic trading platforms, risk management systems, market risk, counterparty risk, algorithmic trading, data analytics, and Regulatory measures. The use of advanced technologies like API's, artificial intelligence and cloud solutions are also becoming increasingly prevalent in capital markets to enhance efficiency and decision-making processes.
Job Responsibilities :
- Identify and create relevant features from transaction data to improve model performance.
- Perform feature selection and dimensionality reduction to enhance model efficiency.
- Develop, train, and evaluate machine learning models using transaction data.
- Implement cross-validation and hyperparameter tuning to optimize model performance.
- Monitor model performance over time to detect and address issues such as data drift and model degradation.
- Implement model retraining and updating processes to maintain model accuracy and relevance.
- Develop and execute strategies to integrate Generative AI tools and techniques into transaction data monitoring processes, improving efficiency and reducing development time.
- Design tests and refining prompts for LLM to improve accuracy, reliability and efficiency.
- Identify opportunities to augment data science workflows using GenAI, enhancing model development, data analysis, and feature engineering capabilities.
- Collaborate with data engineers, software developers, and business analysts to ensure seamless integration of data quality monitoring processes.
- Work closely with domain experts to understand transaction data requirements and business rules.
- Effectively communicate data quality findings, model performance, and project progress to stakeholders.
- Provide actionable insights and recommendations to improve data quality and model performance.
- Maintain comprehensive documentation of data quality monitoring processes, machine learning models, and generative AI models and processes.
- Document data preprocessing steps, feature engineering techniques, and model evaluation results.
- Stay updated with the latest advancements in machine learning, generative AI, and data quality monitoring techniques.
- Experiment with new tools, technologies, and methodologies to enhance data quality monitoring and model performance.
Your profile
Job Requirements:
- Candidates should have a minimum of 6 years' experience in relevant activities
- At least Bachelor's Degree in Computer Science, Information Technology, Programming & Systems Analysis, Science (Computer Studies) or related fields.
- Proficiency in languages such as Python, R, SQL, and Java or Scala.
- Strong understanding of statistical methods and concepts.
- Experience with data manipulation libraries (e.g., pandas, dplyr) and data analysis tools.
- Knowledge of machine learning algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
- Expertise in analyzing and forecasting time series data.
- Ability to create visualizations using tools like Matplotlib, Seaborn, ggplot2, or Tableau.
- Big Data Technologies: Familiarity with big data tools such as Hadoop, Spark, and distributed computing.
- Database Management: Experience with relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB, Cassandra).
- Docker/Kubernetes, Kafka, Spark, Mongo DB
- Data Wrangling: Skills in cleaning, transforming, and preparing data for analysis.
- Knowledge on implementing ML and GenAI solutions AWS (Bedrock, SageMaker etc.)
- Experience in supporting capital market applications and trading systems, ideally within the dynamic landscape of Market Risk/Front Office operations with a commendable grasp of financial products (Treasury, FX, Credit, IRD, Bonds, RSF etc.).
- Experience in Business intelligence tools
- Experience in working with application monitoring and automation
- Experience in Banking environment, especially in Capital Market IT
About Antaes
Founded in 2007, Antaes is a Swiss management and technology consulting company ranked among the top 15 consulting firms in Switzerland. We employ over 300 experienced consultants who share our passion.
With offices in Switzerland, Singapore, Hong Kong and France, we support our Swiss and international customers at clients in the following areas:
- Organization and transformation consulting
- Industrial Engineering
- Information Systems Management
By joining our teams you will discover :
- A dynamic team in a start-up spirit
- Human support and career development monitoring
- Challenges to help develop your network
- Events: team building, meet-up, workshop, Winter Event ...
-
An @HappyAtWork certified company with a committed CSR policy (Ecovadis2023 Gold Medal)
