Data Scientist Capgemini Engineering

About Capgemini Engineering

Job Description

You will be joining Capgemini Engineering as a Data Scientist, a global leader in engineering services, where you will work alongside a diverse team of engineers, scientists, and architects to empower innovative companies worldwide. As a Data Scientist at Capgemini Engineering, you will need to possess expertise in Cognite Data Fusion, data modeling, Unified Namespace (UNS), ontologies, and the ability to identify data products and datasets. Your role will involve developing and implementing data science projects, analyzing large and complex datasets, and driving data-driven decision-making initiatives within the organization. Your responsibilities will include designing, implementing, and deploying scalable data solutions using Cognite Data Fusion, with a focus on data modeling, UNS, and ontologies to address industry-specific challenges. You will also be responsible for analyzing large datasets to uncover trends, insights, and opportunities that support solution development and business strategies. Collaboration with cross-functional teams to understand data needs and translating them into data science solutions will be essential, ensuring seamless integration and operationalization of digital solutions across various domains. Engaging with clients to grasp their business objectives, leading discovery workshops, and providing expert guidance on data-driven strategies and potential challenges will be part of your role. Additionally, you will develop dashboards and visualizations using tools such as Power BI, Grafana, or web development frameworks like Plotly Dash and Streamlit to effectively communicate data insights. Moreover, you will provide guidance and mentorship to junior team members, promoting best practices in data science and software development. To qualify for this role, you should hold a Masters or PhD degree in a quantitative field, have a minimum of 2 years of experience in data science, particularly in domains like pharma, oil and gas, manufacturing, or power & utilities. Proficiency in Python and its data ecosystem, machine learning libraries, SQL, and experience with data visualization tools are necessary. A strong understanding of software development practices, cloud platforms, and industrial data management concepts is advantageous. Excellent communication and collaboration skills, coupled with leadership abilities, are also important for this position. Preferred qualifications include industry expertise, experience in deploying models in production environments using cloud infrastructure, and a willingness to stay updated with the latest developments in data science and related technologies.,