
Senior Data Scientist (Remote or on-site)
RemoteLugano, Ticino, Switzerland
Job description
PLEASE NOTE: This position can be either:
a 100% remote position for full-time contractors or employees located in Europe (within the time zones UTC to UTC+2). A trip to our office in Switzerland (expenses paid by the company) one week per quarter, to work onsite with the team, is required.
based in our Swiss HQ in Mendrisio, Switzerland, which is 7km over the border from Italy and easily commutable from Milan, Como, Varese or Lugano. We are also happy to assist with your relocation to this beautiful part of Europe and we have a hybrid remote working policy.
About Us
Cloud Academy is a hyper-growth upskilling and reskilling SaaS company, focused on enabling enterprise customers to have full transparency and control over their tech workforce skills readiness. In a rapidly changing cloud technical landscape where there is an increasing tech skills gap in the market, combined with the difficulty organizations are facing to retain tech talent and the demands for numerous technical certifications, companies need the ability to manage these skills at scale more than ever. We help over 1000 customers visualize, assess, transform and measure their teams’ tech skills readiness through a unique Skills Intelligence Platform, powered by world-class cloud training content. Companies like Warner Media, Deloitte, JP Morgan Chase, and Walmart trust Cloud Academy with their technical cloud skills readiness at scale, so they can achieve their cloud business goals. We are a global team, with colleagues in over 14 countries worldwide. We are a diverse team that is innovative, collaborative, pragmatic and passionate about making an impact. We thrive on a common vision, we obsess about our customers and learners, and we take pride in the quality of our work. Most importantly, we know that individually we are only as good as our teams are, and we always have each others’ backs. We are seeking driven, highly competent, and creative team players to join us on the next phase of our growth story, as we scale our winning products to help even more customers and learners.
We are currently expanding our dedicated Data & Machine Learning team with a highly motivated, self-directed Senior Data Scientist who is passionate about applying critical thinking and creativity to data in real scenarios, developing data-driven applications, and processing structured and unstructured data to extract insights to support business decisions. The team works in synergy with the Engineering and Product teams and has active collaborations with universities and researchers.
The candidate will be involved in the challenging activities of the team, serving both internal and external stakeholders. This includes, among others:
UX personalization through content recommendations
Skills assessment to measure and fill user’s knowledge gaps
Assistance and automation to content creation (NLP/NLG)
Detection of fraudulent activities on the platform
Extraction of insights through data analysis
Role Description
The Senior Data Scientist will join the Data Science squad, and act as a technical point of reference for the whole squad. Main requirements include:
- Acquiring and maintaining context on all major projects of the squad, strongly contributing to its operative maintenance and well-functioning, as well as its iterations and evolution. Projects include:
Data Analyses (ad hoc analyses, pipelines for report generation)
Deployed ML services (recommendations, skill evaluation, automation/assistance in content creation)
- Supporting the Data Science Manager in defining a technical roadmap for the next quarter/semester/year. This includes also:
Evaluating improvements of existing functionalities
Proposing new functionalities
Collaborating with the Data Engineering squad to ensure that data products are powered by high quality data, using Data Engineering best practices
Mentoring colleagues, providing technical guidance and helping them remove execution blocks in their day to day work
Interacting with stakeholders of the Data Science squad to understand requirements, define interfaces, communicate progress and ensure adoption
Job requirements
B.Sc/M.Sc in a quantitative field
5+ years of experience in the role
Good grasp of Statistics Fundamentals and Exploratory Data Analysis
Proficient with Python for Data Science (pandas, numpy/scipy, sklearn)
Familiarity with cloud services for ML deploy and training (AWS Sagemaker, Azure Machine Learning, etc.) and experience performing deploys
Attitude towards debugging/understanding root cause of problems
Experience with 2+ ML domains: Recommendations, Fraud Detection, Natural Language Processing / Generation, User Profiling
Problem Solving & Critical Investigation skills
Mentoring/coaching attitude and passion for sharing knowledge with the team
Collecting and handling ambiguous requirements
Attention to metrics and demonstrable results
Interest in building services that strongly integrate with a user-facing product
Drive to expand to new applications and domains, keeping up to date with new technologies
Nice to have
Ph.D. in a quantitative field
Familiarity with cloud services for web development
Python for Deep Learning (pytorch, TF, other)
Tools for ML model lifecycle management (MLFlow, comet.ml, WandB)
Basics of Data Engineering
Ability to set up interactive dashboards
Experience with 1+ ML domain: Skill Assessment, Churn Prediction
Experience managing people
Passion for external knowledge dissemination (blog posts, research papers, webinars
Benefits
Competitive compensation and a bonus plan
Four weeks of paid vacation per year (that increases to five weeks after two years with the company!) plus one day off per year to volunteer at your favorite non-profit
Equality & Diversity
We pride ourselves on being an equal opportunity employer, committed to equality and diversity amongst both our employees and prospective applicants. We ensure that all applicants are treated equally and fairly throughout our recruitment process. We are determined that no applicant experiences discrimination on the basis of sex, race, ethnicity, religion or belief, disability, age, gender identity, ancestry, sexual orientation, veteran status, marriage and civil partnership, pregnancy and maternity, socio-economic background, neuro-diversity, education, or any other basis prohibited by applicable law.
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