Data Scientist / Machine Learning Engineer

Summary

As a Data Scientist / Machine Learning engineer, you will play a key role in developing end-to-end solutions for machine learning use cases. By taking up a use case right from the start you will help business define and scope the problem, pick the right machine learning solution and technology as well as ensure implementation, integration and deployment of your solution to production. You will do so while ensuring that our internal governance processes and best practices are respected. You will also collaborate with other team members in knowledge sharing as well as continuously improving our way of working.

Key Responsibilities:

• Translate business requests into data requirements, extract the required structured and unstructured data from the global company data lake, data warehouse and other data sources (e.g. operational systems) and prepare large-scale datasets for modelling.
• Identify high-value use cases through data exploration and visualization.
• Develop predictive models using state-of-the-art machine learning and statistical methods.
• Pilot prototypes in production processes to demonstrate their value.
• Deploy prototypes to production, with support of IT, to obtain reliable, scalable systems.
• Present your results in a clear manner and discuss them with multi-functional project teams.
• Work in close collaboration with business experts (e.g. for requirement gathering, data source identification, data and process understanding, feature engineering, result validation, etc.), with IT (e.g. for ETL, deployment to production, etc.) and with other machine learning engineers in the team (e.g. for knowledge sharing).

Degree & Experience Requirements:

• PhD or Master's degree in a quantitative field (Artificial Intelligence, Computer Science, Engineering, Statistics, Mathematics, etc.)
• 3+ years of relevant work experience in a business environment
• Fluent in English language

Technical skills Requirements:

• Strong knowledge of state-of-the-art machine learning and statistical methods.
• Hands-on experience with Python and its machine learning ecosystem. Experience with deep learning (e.g. Tensorflow, PyTorch), big data (e.g. Spark, Hadoop) and real-time streaming is a plus.
• Experience with developing end-to-end ML projects on AWS and Databricks
• Proven proficiency in the end-to-end machine learning project life cycle, including:
  • Translating business requests into data requirements.
  • Identifying high-value use cases through data exploration and visualization.
  • Developing machine learning solutions (incl. feature engineering, model fitting, monitoring, versioning etc.).
  • Proficiency in using Git for version control and collaborative development within a team environment.
  • Understanding of software development best practices, including code reviews, testing and documentation.
  • Deploying scalable machine learning applications to production.
• Any experience with following elements is a big plus:
  • MLOps practices, e.g. orchestration with Airflow, Gitlab CI/CD, etc.
  • Containerized deployment of ML products – e.g. docker, podman, Kubernetes

Attitudes/Behavior Requirements:

• Passionate about machine learning and a constant learner
• Result-oriented and highly proficient in transforming data into actionable insights that create business value
• Proactivity with a strong sense of ownership over projects
• Excellent problem-solving skills and attention to detail
• Team player with strong communication and presentation skills
• Able to manage machine learning projects in an autonomous way and drive collaboration with domain experts, data engineers and other machine learning engineers
• Experience working with Agile methodologies, particularly Kanban, to effectively manage and deliver project tasks
• Knowledge in the field of telecommunications is a plus

We are offering:

• Good compensation - Competitive € salary plus benefits package. 
• Development opportunities. 
• Challenging but also a friendly working environment. 
• And much, much more... 

About Telesign: 

Telesign connects and protects online experiences with sophisticated customer identity and engagement solutions. Through APIs that deliver user verification, data insights, and communications we solve today’s unique customer challenges by bridging businesses to the complex world of global telecommunications. 

Telesign is proud to be an equal opportunity employer. We believe our differences help us create a better workplace, a better product, and a better community. We do not discriminate on the basis of race, color, ancestry, religion, national origin, marital status, pregnancy, sex, sexual orientation, gender, gender identity or expression, age, genetic information, disability, military or veteran status, or any other basis protected by federal, state or local law, ordinance or regulation. 

Telesign is an Affirmative Action Employer and as part of the commitment to AAP, it will seek to ensure affirmative action to provide equality of opportunity in all aspects of employment, and that all personnel activities, such as the recruitment selection, training, compensation, benefits, discipline, promotion, transfer, layoff and termination processes remain free of illegal discrimination and harassment based on protected characteristics.