Data Scientist @HN Services Romania (DO)
HN Services, a company specialized in digital transformation and software development, has 35 years worldwide presence, with offices in Romania (Bucharest), France (Paris, Marseille, Aix en Provence), Portugal (Lisbon and Porto), Spain (Madrid),) and Luxembourg, with over 1200 employees.
HN Services Romania has strengthened its local presence since 2006, always being guided by values such as commitment, communication, closeness towards its employees and partners, openness, agility and involvement. We like to recommend ourselves as having the mindset of a company and the agility of a start-up.
With its own Training Center, HN Services Romania contributed to the professional reconversion of more than 200 specialists in Cobol, Java and .NET. We develop projects for various industries from banking to automotive, mainframe (Cobol), Java, .NET, Android, iOS, Salesforce, etc.
Under the slogan #changethecode, we make a difference in the way we work, recruit and in the relationship with our partners and employees. We invite you to find more about us on our LinkedIn page or on Facebook.
• General role: Develops Data Science use cases to solve business problems with analytics solutions.
• General responsibility: Analysis of business needs requiring an analytical approach, construction of the corresponding machine learning algorithms and integration of these solutions into products.
• General skills: descriptive statistics, machine learning algorithms, data visualization, code development, distributed data processing.
• You are part of the Data Pole, headed by the Chief Data Officer and reporting to the Chief Digital Officer. Via proactive interviews with Company businesses or in the upstream phase of the project, you analyze business issues and needs to design potential analytical solutions. In the project phase, you design, experiment, build and implement these solutions in production, using your solid technical know-how and your understanding of the context
Upstream of a project:
• Collaborate with the various company players, both business and technical, to imagine innovative analytics solutions and identify synergies between projects.
• Analyze the quality and availability of a project's data sources.
• Analyze data and test algorithms to estimate the feasibility of a project.
During the project phase:
• Participate in the life of a project, with its different members, technical, business, IT, UX, agile.
• Analyze and understand in detail the business problem.
• Data engineering and feature engineering.
• Create precise and efficient analytical models.
• Document and present the models and their parameterization.
• Develop and integrate models in production, from data preparation to prediction.
• Define and document the tests related to the model (re-training, drift).
In non-project phase:
• Peer validation and support for the approaches and models of data scientists from other projects.
• Technology watch and continuous learning.
• Participate in company's Data acculturation (presentation content and training).
• Participate in the recruitment of new Data Scientists.