Project Description
We are seeking a talented Data Scientist to join our dynamic Capital Market Department!
As an Data Scientist, you will be responsible for participate in development, training,deployment and management of data quality monitoring modelsusing 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 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.
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 test and refine 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.
Mandatory Skills Description:
• 6+ years of experience in relevant activities.
• 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.)
• 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/Kubernete, 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..)
• Excellent communication and interpersonal skills to effectively collaborate with diverse teams.
• Excellent problem-solving and analytical skills.
• Ability to work under pressure.
• Appetite to follow technology trend and participate to communities.
• Eagerness to learn and adapt to new technologies.
• Strong perseverance and diligence towards attaining goals and effective time management
• Passion for sharing expertise and grow team members' skills.
Project Description
We are seeking a talented Data Scientist to join our dynamic Capital Market Department!
As an Data Scientist, you will be responsible for participate in development, training,deployment and management of data quality monitoring modelsusing 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 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.
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 test and refine 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.
Mandatory Skills Description:
• 6+ years of experience in relevant activities.
• 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.)
• 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/Kubernete, 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..)
• Excellent communication and interpersonal skills to effectively collaborate with diverse teams.
• Excellent problem-solving and analytical skills.
• Ability to work under pressure.
• Appetite to follow technology trend and participate to communities.
• Eagerness to learn and adapt to new technologies.
• Strong perseverance and diligence towards attaining goals and effective time management
• Passion for sharing expertise and grow team members' skills.