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The position in a nutshell:
We are looking for a Data Scientist who is passionate about developing and applying Advanced Analytics techniques to generate business value.
The Data Scientist will work cross-functionally closely with all the main stakeholders in Orange Romania (Finance, Marketing, B2B, Sales & Distribution, Technology, HR etc.), in order to successfully build and operationalize E2E applications underpinning business use cases, using predictive analytics modeling.
The position is part of the AI, Big Data & Automation vertical inside the Enterprise Data Management & Analytics Division.
Main responsibilities and activities:
- Solve a large pool of business problems articulated in the form of the value generating use cases, by leveraging mathematical, statistical and econometric techniques to perform trends analysis, identify patterns and correlations, etc.
- Lead processes of analytics value use cases identification, financial valuation and benchmark across different business units, acting as business partner and liaising with analysts, product owners and business owners
- Munge, mine, wrangle and analyze structured and unstructured data from company databases, either primary systems databases, Data Warehouse and Big Data infrastructures or other external data sources; support the data engineering process for data structuring, modeling and ingestion across a variety of data sources
- Apply Advanced Analytics / Data Science techniques to build prototype models; apply experimentation techniques (A/B testing, multivariate testing, etc.) to learn and adjust iteratively for continuous improvement of models performance
- Drive the E2E operationalization and integration of the prototype analytical models into the existing Orange Romania Data Management & Analytics ecosystem of applications, databases and other systems and/or platforms
- Manage a pipelineof concurrent running models in batch or real time mode, as well as the Advanced Analytics toolkit, proprietary and open source
- Functionally document models in the Advanced Analytics knowledge base
- Coordinate with different functional teams to implement new data models
- Develop Advanced Analytics competences and capabilities within the team and other functional areas across the company
The ideal candidate needs to have:
1. Key Technical Skills:
- Mastery of Advanced Analytics techniques & algorithms (descriptive, predictive, causal, prescriptive and cognitive) with strong focus on applicability in solving different business problems
- Full range of Machine Learning, AI/Deep Learning and neural nets, Natural Language Understanding & Processing, Text/Speech Analysis, etc.
- Knowledge of mathematics statistical techniques and concepts (properties of distributions, hypothesis testing, statistical tests and proper usage, model evaluation etc.) and experience with applications
- Knowledge of ML algorithms (regressions, classifiers, clustering, dimensionality reduction)
- Model prototype building using open source languages – Python or R, as well as enterprise data science tools - SAS Viya/Enterprise Miner
- Basic SQL / PL-SQL experience
- Agile/Scrum Project Management
- Microsoft Office suite, i.e. Excel (including functions, pivot tables, graphs, etc.), PowerPoint
2. Key Soft Skills:
- Strong communication (oral, written), storytelling and analytical skills, high degree of accuracy and attention to details; ability to quickly grasp new concepts, understanding solution architecture and involvement in system design
- Open minded and able to adapt to frequent changes; can-do attitude, proactivity
- Team player eager to work in a fast paced IT&C environment in Agile cross-functional setups
- Autonomous and problem-solving oriented, gives multiple alternatives when asked to solve a problem (including anticipation and problem definition skills)
- Openness and desire towards business understanding and learning
- Strong presentation skills and customer centricity; capacity to translate in natural language the results of a complex algorithm and explain them to business owners
3. Education & Experience
- Technical University degree or background preferred – e.g. majoring in Computer / Data Science, Applied Mathematics - Statistics, IT, Engineering field (PhD or MSc a plus)
- Min. 2 years in a Data Science/ML Engineer role or similar experience
- Fluency in English (oral and written)
Nice to have (not mandatory, but any one of them considered a plus):
- Knowledge of Telecom industry, market and businesses, corresponding data models and / or previous data modelling experience
- IT&C Business Analyst or Data Analyst background
- Business Intelligence & data visualizationusing SAP Business Objects, Tableau and/or QlikView
- Integration and automation coding - APIs and Web services design and build
- Knowledge of the following Python modules (pandas, numpy, sklearn, tensorflow/pytorch)
- Experience with software versioning systems such as git
- Databases know-how, such as Oracle Data Warehouse, Hadoop Big Data/NoSQL databases
- Know-how of software development lifecycle, techniques such as TDD/BDD, automated CI-CD, DevOps; ML pipelines and containerization (Docker, Kubernetes)
- Decision-making and decision intelligence
- Cloud computing
- Data extraction and processing skills, using Map Reduce, Pig, and/or Hive; experience with Spark and Scala languages
Număr Post: GTAO917767
Dată limită: 18/12/2019
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