Main tasks for the Data Scientist Specialist will be:
Working with business stakeholders throughout the organization to identify prospects for leveraging company data and driving business solutions
Mining and analyzing data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies
Assess the effectiveness and accuracy of new data sources and data gathering techniques
Develop, deploy and maintain custom data models and algorithms to apply to data sets
Using predictive modeling to increase and optimize manufacturing processes, product quality and other business processes
Develop testing framework and test model quality
Coordinating with different functional teams to implement models and monitor outcomes
Develop processes and tools to monitor and analyze model performance and data accuracy
Using expertise in coding, algorithms, complexity analysis and large-scale system design while keeping a results oriented approach
The Candidate should :
Have self-driven, autonomous, results oriented attitude
Enjoys solving business and technical challenges
Be a positive and joyful person including under stress
Have curiosity to explore, to learn new things and to challenge existing understandings
Design solutions, the end result and all the intermediate elements
Build solutions to be reliable, secure, sustainable and performant while remaining pragmatic in achieving the intermediate objectives
Have a courage to take risks, openness to admit errors and move forward by learning from errors
Perseverance in face of setbacks
Team and detail-oriented, productive and solution-oriented attitude
Analytical and problem solving skills
Great communication and interpersonal skills
Flexibility and ability to work independently and also in a team
Have knowledge about machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Be familiar with advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Have excellent written and verbal communication skills for coordinating across teams (also in English)
Be eager to learn and master new technologies and techniques
5-7 years of experience manipulating data sets and building statistical models, has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field
The Candidate should familiar with the following software/tools:
Experience querying databases and using statistical computer languages to manipulate data and draw insights from large data sets: R, Python, SLQ, etc.
Experience using major cloud providers (for machine learning training / ML-OPS pipelines) like AWS, Azure, GCP,…
Be experienced in using web services: Redshift, S3, Spark, Digital Ocean, etc.
Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, anomaly detection, decision trees, neural networks, etc.
Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
visualizing/presenting data for stakeholders: Periscope, Business Objects, D3, ggplot, etc.
It would be nice if the Candidate had experience with developing and deploying machine learning models for the heavy/process manufacturing industries like cement, steel, paper, oil, mining etc.
The Candidate can expect:
Challenging job in an international and multilingual environment
Attractive and competitive compensation