Data Scientist

Leverage data science and business domain knowledge to improve business performance, evaluate project plans, communicate business goals, and share insights with stakeholders Acquire, prepare, and explore data through querying, visualisation, reporting techniques, and collaboration with other teams, ensuring data integrity. Apply machine learning and statistical analysis to develop models, train, optimise, and evaluate them, and communicate findings to stakeholders. Test, review, and improve models by analysing performance, incorporating feedback, and contributing to the review process. Write and debug efficient and scalable code while collaborating with engineering teams and integrate data models into customer systems. Evaluates project plan for resources, risks, contingencies, requirements, assumptions, and constraints. Collaborates with others to perform data-science experiments using established methodologies and tools. Designs experiments, analyzes results, and communicates findings to stakeholders. Learns and understands the current state of the industry, including knowledge of tools, techniques, strategies, and processes that can be utilized to improve process efficiency and performance. Maintains knowledge of current trends within the discipline. Attends internal research conferences and participates in on-hands training, when appropriate. Actively contributes to the body of thought leadership and intellectual property (IP) best practices. Coding and Debugging Writes efficient and readable code for specific features, collaborating with other engineering teams to optimize code and improve system efficiency, reliability, and maintainability. Develops expertise in debugging techniques and integrates data models into customer systems. Understands big-data software engineering concepts, such as Hadoop Ecosystem, Apache Spark, CI/CD, Docker, Delta Lake, MLflow, AML, and REST API consumption/development. Business Management Develops understanding of data structures and relationship to customer business goals, observes senior engineers for best practices in identifying growth opportunities and exploring ML applications. Understands customer business goals and demonstrates a strong commitment to Responsible AI, supporting customers, partners and internal stakeholders in building trustworthy AI solutions. Customer/Partner Orientation Focuses on customer needs, manages expectations, and enhances customer excellence. Learns from senior team members to develop insights and communicate results. Understands the impact of data quality on model accuracy and can explain it to customers. Other Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, Operations Research, or a related field, with proven 4 years of data science experience in business context. Be able to work independently, solve complex data science problems, design and code maintainable and scalable solutions, and effectively apply data science to business challenges. Hands-on software engineering experience (e.g. Python, Scikit, PyTorch,C++) with main established data science frameworks. Familiarity with building and deploying largescale AI solutions into production within a cloud environment Experience dealing with internal and external stakeholders on large, complex projects.