.With a $150 million funding round received recently from Insight Partners and impressive yearly revenue growth, Lansweeper is rapidly expanding its Global teams. We now need a Senior Platform Engineer to help us scale and to take Lansweeper to the next level.Lansweeper is an IT asset management software helping businesses better understand, manage and protect their IT devices and network. We currently discover and monitor around 100 million connected devices from 25,000+ customers, including Mercedes, FC Barcelona, Michelin, Sony, Carlsberg, Nestlé, IBM, Maersk and Samsung to governments, banks, NGOs, and universities, driven by its 150+ strong teams in Belgium, Spain, Italy, Ireland, UK and the USA.Over 90% of our customers renew their subscriptions every year and we onboard 250 new customers every month. Our high-performance/high-reward culture emphasizes improvement and progress. Under the "work hard, play hard" motto we want employees to grow professionally through ongoing learning and taking on new challenges. Discover more about Lansweeper impressive growth on this video.If you believe you have what it takes to help us take Lansweeper to the next level contact us now!We are seeking an experienced and highly skilled Senior Data Scientist to join our dynamic team. The ideal candidate will possess a deep understanding of data analysis, statistical modeling, and machine learning techniques. This role involves leading data science projects, developing and optimizing machine learning models, and providing strategic insights to drive business decisions.Key Responsibilities- Leadership & Strategy:- Lead the development and execution of complex data science projects from ideation to deployment.- Develop and implement data science strategies that align with business objectives and drive impactful outcomes.- Mentor and guide junior data scientists, fostering a culture of learning and collaboration.- Data Collection & Preparation:- Oversee the collection, cleaning, and preprocessing of data from various sources to ensure data quality and integrity.- Conduct exploratory data analysis to uncover insights, patterns, and trends.- Model Development & Innovation:- Design, develop, and implement advanced machine learning models to address complex business challenges.- Employ a variety of supervised and unsupervised learning techniques, including deep learning, natural language processing (NLP), and reinforcement learning.- Innovate and explore new methodologies to advance our machine learning capabilities.- Model Evaluation & Optimization:- Evaluate model performance using robust metrics and validation techniques.- Optimize models for accuracy, efficiency, scalability, and interpretability.- Implement model monitoring and maintenance to ensure long-term effectiveness
