Senior Data Scientist (m/w/d)

at  ILIDIGITAL

ILI.DIGITAL AG, a leader in digital transformation and innovation, is seeking an experienced and dynamic Senior Data Scientist to join our team in Karlsruhe. We specialize in creating cutting-edge digital solutions across various industries including automotive, chemical, consumer goods, and financial services. Our mission is to harness the power of data and AI to drive strategic and impactful digital transformations for our clients. The role involves developing statistical models, managing big data, and collaborating with cross-functional teams to drive digital transformation. Ideal candidates will have a Master’s or PhD in a related field, proficiency in Python, R, and SQL, and strong problem-solving skills. Benefits include a competitive salary, professional growth opportunities, and flexible working hours.

Responsibilities

• Advanced Analytics & Modeling: Lead the development and implementation of advanced statistical models and machine learning algorithms to solve complex business problems.
• Data Strategy: Design and execute data-driven strategies that align with business objectives, enhancing operational efficiency and decision-making processes.
• Big Data Management: Oversee the collection, storage, processing, and analysis of large and complex datasets using state-of-the-art technologies and methodologies.
• Collaborative Innovation: Work closely with cross-functional teams, including software engineers, data analysts, and business stakeholders, to deliver innovative data solutions.
• Leadership & Mentoring: Provide guidance and mentorship to junior data scientists, fostering a culture of continuous learning and professional development.
• Technical Expertise: Stay updated with the latest advancements in data science and AI, applying this knowledge to improve existing models and methodologies.
• Client Engagement: Communicate insights and recommendations to clients, helping them understand the implications of data findings and how they can be leveraged to drive business growth.

Requirements

• Educational Background: Master’s or PhD in Computer Science, Data Science, Statistics, or a related field.
• Experience: At least 5-7 years of professional experience in data science or related roles, with a proven track record of leading projects from conception to deployment.
• Technical Skills: Proficiency in programming languages such as Python, R, and SQL. Experience with big data tools and machine learning frameworks (e.g., TensorFlow, PyTorch).
• Analytical Skills: Strong analytical and problem-solving skills, with the ability to interpret complex data and provide actionable insights.
• Communication Skills: Excellent verbal and written communication skills, capable of explaining technical concepts to non-technical stakeholders.
• Project Management: Demonstrated ability to manage multiple projects simultaneously, delivering high-quality results within deadlines.

Key Benefits

• Competitive Salary
• Professional Growth
• Work-Life Balance
• Innovative and International Environment
• Health and Sport Care Package

Job ID 94141

• Advanced Analytics & Modeling: Lead the development and implementation of advanced statistical models and machine learning algorithms to solve complex business problems.
• Data Strategy: Design and execute data-driven strategies that align with business objectives, enhancing operational efficiency and decision-making processes.
• Big Data Management: Oversee the collection, storage, processing, and analysis of large and complex datasets using state-of-the-art technologies and methodologies.
• Collaborative Innovation: Work closely with cross-functional teams, including software engineers, data analysts, and business stakeholders, to deliver innovative data solutions.
• Leadership & Mentoring: Provide guidance and mentorship to junior data scientists, fostering a culture of continuous learning and professional development.
• Technical Expertise: Stay updated with the latest advancements in data science and AI, applying this knowledge to improve existing models and methodologies.
• Client Engagement: Communicate insights and recommendations to clients, helping them understand the implications of data findings and how they can be leveraged to drive business growth