The Lead Data Scientist is a new role in ROCKWOOL created to help accelerate and steer ambitious Data Science initiatives. ROCKWOOL has vast potential in data from production, sales, marketing, logistics – and a lot more. The Lead Data Scientist will work strategically shaping the data science landscape, solutions and roadmaps that are needed to succeed with the goal of getting unique customer and market insight, as well as achieving operational excellence through IOT, analytics and algorithms. The Lead Data Scientist will also be a hands-on person getting engaged in concrete projects, advising and driving data science projects in our different functions.
Data Science will be a growing capability for ROCKWOOL and the Lead Data Scientist will be a key member growing the capability through increasingly advanced tools and skills and new team members.
Primary tasks and areas of responsibility:
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- Mine and analyze data from company databases and data lakes to drive optimization and improvement of customer experience, product development, marketing techniques and business strategies.
- Assess the potential and accuracy of new data sources and data gathering techniques. Design and set requirements for data science landscapes and govern its implementation.
- Develop custom data models and algorithms to apply to data sets.
- Use predictive modeling and build algorithms to optimize manufacturing processes, asset maintenance and logistics.
- Engage with external consultancies and companies working on innovation and projects.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Leading and directing other Data Science Team members as well as identifying and lead development of the Data Science Capability
REQUIRED SKILLS AND EXPERIENCE
The ideal candidate has experience of building data science landscapes and solutions that deliver the needed data and labs to the business analyst. Namely experience working with sensor data from production environments is a plus. The candidate is very experienced in using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.
Furthermore, the ideal candidate has strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. You have a proven ability to drive business results with data-based insights. You are comfortable working with a wide range of stakeholders and functional teams and have a passion for discovering solutions hidden in large data sets.
Additionally, you have:
- Management skills (3-5 years) managing teams or projects.
- Strong problem-solving skills with capability to deliver operational results.
- Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
- Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
- Experience working with and creating data science architectures.
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Excellent written and verbal communication skills for coordinating across teams.
- A drive to learn and master new technologies and techniques.
5-7 years of experience manipulating data sets and building statistical models as well as a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field is expected.
Furthermore, familiarity with the following software/tools is vital:
- Advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
- Analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
- Distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
- Visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3,ggplot, etc.
The ROCKWOOL Group is the world’s leading manufacturer of stone wool insulation, offering a
full range of high-performing and sustainable insulation products for the construction industry.
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