Data Scientist

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.

• Collaboration & Communication:
• Collaborate with cross-functional teams, including data engineers, software developers, and business stakeholders, to understand requirements and deliver impactful solutions.
• Communicate complex technical findings and insights to non-technical stakeholders in a clear and concise manner.

• Research & Continuous Learning:
  • Stay current with the latest advancements in machine learning, data science, and related fields.
  • Lead research initiatives and contribute to the continuous improvement of our data science practices.

Qualifications

• Education:
• Degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.

• Experience:
• 5+ years of experience in data science and machine learning, with a proven track record of successful projects.
• Extensive experience with machine learning frameworks such as TensorFlow, Keras, PyTorch, or scikit-learn.
• Proficiency with data visualization tools such as Tableau, Power BI, or matplotlib.

• Skills:
  • Advanced programming skills in Python or R.
  • Expertise in SQL and experience with relational and non-relational databases.
  • Deep understanding of statistical methods and data analysis techniques.
  • Familiarity with big data technologies such as Hadoop, Spark, or cloud-based data services.
  • Strong problem-solving skills and attention to detail.
  • Excellent leadership, communication, and collaboration abilities. (Spanish and English)

Preferred Qualifications

• Experience with advanced techniques such as natural language processing (NLP), deep learning, and reinforcement learning.
• Knowledge of cloud platforms (AWS, Google Cloud, Azure) and their machine learning services.
• Experience with version control systems, such as Git.
• Familiarity with Agile methodologies and project management tools like Jira.

Our offer you can't refuse