Job Details

Data Scientist

MBR Partners
MBR Partners

Data Scientist
Location: Paris, La Defense

Main purpose of role
The Data Scientist contributes to company’s success by executing Data Science and putting in place the data science practice within the organization while collaborating with telecommunications customers, partners, product managers, software architects and engineers across the globe to develop, manage, and improve the outputs of Descriptive, Predictive and Prescriptive models and statistical analysis to ultimately develop a machine learning and artificial intelligence product line fuelling the rest of the the Company's product portfolio. The model outputs will allow customers to better predict and automate repetitive service assurance tasks like predicting failures/bottlenecks and root causes. Key Role Responsibilities
You will be leading and pioneering the exploration, development and evaluation of new algorithms and technologies to resolve specific business problems related to our industry. With the objective of taking the AI/ML research studies and results from concept to production-quality code ready for deployments at our customers. Our projects cover many fields of computer science including supervised & unsupervised machine learning, natural language processing, anomaly detection and graph theory.

It is a great opportunity for you to discover a faster than ever moving Telco industry and where the AI/ML is a key promising and must have enabler to address industry challenges. We are creating our Data scientist department and you will be playing a strategic role in the digital transformation and disruptive innovation we are creating.

Who we are looking for people:
• Eager to learn attitude for logical problem solving skills
• Enthusiastic, can-do attitude who can work independently as well as contribute with the team
• Strong communication skills both within and outside teams.
• Demonstrable software engineering experience from previous internship, work experience, coding competitions, or publications preferably in Java, Python, Spark or KNIME as a plus.
• Any involvement in a project to implement a machine learning model from scratch would be a distinct advantage
Responsibilities and essential job functions include but are not limited to the following:
• Designs experiments, test hypotheses, and build descriptive, predictive and prescriptive analytics models fulfilling well defined Telecoms Assurance, Analytics and Automation use cases making use of classical and advanced machine learning and neural networks algorithms and approaches
• Works with internal and external stakeholders to identify/detail the requirements/use cases and the expected outcome both technical and business
• Manage ML/AI Proof Of Concepts projects with strategic customer and prospects through a scientific and well documented approach allowing to report on advancements and results to internal and external stakeholders having no data science skills
• Leads advanced data analysis and complex designs through carefully selected tools aligned and integrated with the Company's product architecture and architectural vision
• Works with and alongside Product Line Managers/Subject Matter Experts/Solution Architects as domain data knowledge reference and to formulate product/solution strategies (integration, business processes, operationalization)
• Collaborate with R&D Software Architects/Developers and contribute to the integration design and implementation between Data Science / analytics engine and other the Company's Software components driven by end-to-end analytics use cases
• Evangelize and train the Company's developers and Engineers to applied use of AI/ML techniques and selected tools and overall be the referent across the organization for AI/ML related matters
• Monitor and possibly participate to IT and Telecom Standard Organization and Open Source Software projects contributing to defining standard Analytics Models, APIs and promoting the Company's AI/ML driven Use Cases if necessary

The Person
Skills (technical and non-technical) & Qualifications
Must have
• Demonstrates the following scientist qualities: clarity, accuracy, precision, relevance, depth, breadth, logic, significance, and fairness
• Cutting edge experience with cloud based and Big Data advanced predictive modeling and statistical analysis tools being integrated with other software systems using heterogeneous querying and API methods
• Experience in applied data analysis, particularly in applied predictive modeling and statistical analysis solving descriptive, predictive and ideally prescriptive analytics use cases
• Ability to apply knowledge of statistical and mathematical principles to achieve and scientifically demonstrate successful use case outcomes
• Demonstrated experience in using supervised, un-supervised and re-enforcement Machine Learning and Neural Networks algorithms not only in laboratory and experimentation context but commercial and applied applications
• Experience in R statistical modelling language, SCALA and PYTHON and overall familiarity with programing principles and best practices
• Effectively communicate both orally and in writing with adaptability to various levels of knowledge and seniority
• Successfully balance multiple competing priorities and meet deadlines
• Strong attention to detail
• Strong analytical skills
• Proficient in MS Office

• Working knowledge of the telecommunications and networking/IT industry and technologies within fixed and mobile communications
• Significant experience with event and time-series data analytics
• Exposed to Closed-loop and re-enforcement learning involving a strong level of interaction with other systems
• Familiar with software Policy Management principles
• Familiarity with cloud computing and big data technologies.
• Experience with version control platforms (git, svn, etc.)
• Developed skills using Apache Spark Machine Learning Language

Experience & Expertise • Experience with statistical software
• Undergraduate or advanced degree in Statistics, Mathematics, or a related quantitative field
• Completed formal training in statistical and mathematical theory

Key competencies
• Customer Oriented
• Diagnostic Information Gathering
• Analytical, Forward and Conceptual Thinking
• Communication
• Influencing Others
• Results Oriented with attention to detail
• Financial Awareness

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