Data Scientist Specialist

Seargin is looking for a Data Scientist Specialist

• Position: Data Scientist Specialist
• Technologies: Python, R, Hadoop, Cloud Platforms
• Localization: Remote
• Area: Project
• Form of employment: B2B
• Experience Level: Senior

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:

• Coding knowledge and experience with languages like: C, C++, Java, JavaScript, etc..
• 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:

• B2B Contract

• Challenging job in an international and multilingual environment
• Professional development
• Attractive and competitive compensation

If you meet requirements described above, please send your application in English (.doc) at [email protected], stating the name of the position in a subject and/or call +48 789126279.