LogicMonitor is the leading SaaS based performance monitoring platform for enterprise IT.
We love going to work and think you should too. We hold our company culture near and dear – it represents an intermix between passion for leadership and passion for an active, healthy life centered around family and friends. LogicMonitor represents community, collaboration and camaraderie.
Situated in Waterloo, our office is easily accessible by public transportation including train, tube, bus and Overground. Snacks are plentiful, as are the opportunities to do fun things such as company-sponsored recreational activities like yoga, football, and Crossfit. When you join LogicMonitor's London team, you will be working alongside some of the brightest minds with one of the fastest growing, global software firms. We are looking for you to bring your expertise, drive, and passion. This is your chance to join us on our journey as we expand our global presence and achieve record-breaking success.
LogicMonitor is an equal opportunity employer. We're committed to creating an inclusive environment for all our employees, where different backgrounds and perspectives are valued and encouraged - regardless of race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, or sexual orientation.
We operate with integrity, esteem diversity and treat each other fairly and with respect. And we're doing that while nurturing consideration for humanity. We give back to our community and encourage all people to come as they are and find their own version of personal and professional harmony here. We hear time and time again that our awesome people are a huge part of why LMers chose LogicMonitor, love their teams, and choose to stay.
What You'll Do:
This position's main responsibility is to develop innovative techniques that improve the efficiency of IT alert management and achieve better operation outcomes for our customers. Gaining a thorough understanding of the problem area, designing and testing new algorithms, and working with the ML Engineering team to realise and scale the algorithms in production.
The Data Scientist role demonstrates the LogicMonitor core values: Better every day - driving innovation that feeds the continual improvement of our AIOPS solution, and One team, working in lockstep with the ML Engineering team to develop new algorithms into scalable, robust and efficient, production quality workloads.
- Develop a deep understanding of the AIOPS problem domain and desired customer outcomes
- Analyse and measure the effectiveness of current ML techniques for AIOPS
- Identify opportunities to improve customer outcomes through leveraging new approaches and algorithms
- Provide innovative solutions to AIOPS problems, and plan, execute and deliver high quality prototypes to solve these problems
- Be an active member within the ML Engineering team to develop and scale prototypes to production quality implementation
What You'll Need:
- 2-3 years expertise and applied experience in developing and executing machine learning experiments based on a product or business problem
- An understanding of common machine learning algorithms (e.g., classification, regression, and clustering)
- Be curious and enjoy problem solving
- Be proactive in diving into the vast amounts of data we have and contribute your ideas within the support of the AIOPS team
- Practical experience of preparing data for machine learning
- Excellent written and oral communication skills to be able to present your experiment findings to both the AIOPS team and the wider company
- Experience of working with engineering teams to scale prototypes to production quality implementation
- Batchelor's degree in a numeric discipline (e.g. statistics, machine learning, computer science)
- Good programming skills in Python (and/or another coding language) and be able to write clean, maintainable code
Nice to have
- Familiar with Scala, Spark, Kafka
- Docker / Kubernetes
- Knowledge of natural language processing machine learning algorithms
- Familiar with Atlassian Suite (JIRA, Confluence, Bamboo, BitBucket)
- An advanced degree (e.g., MSc, PhD) in a numeric discipline (e.g., statistics, machine learning, computer science)
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