Data Scientist Jobs

Schaeffler is a dynamic global technology company and its success has been a result of its entrepreneurial spirit and long history of private ownership. As a partner to all of the major automobile manufacturers, as well as key players in the aerospace and industrial sectors, we offer you many development opportunities.
Your Key Responsibilities

• Identification and extraction of available and relevant data from internal and external data sources to perform data science solution development.
• Develop custom data models, standard statistical models, machine learning or deep learning algorithms for building diagnostic, predictive and prescriptive data science solution.
• Lead discovery processes with business stakeholders to identify opportunities and business problems and framing them into an IT data science/ advanced data analytics project initiative.
• Perform data cleansing using data processing and statistical software packages.
• Coordinate with different functional agile teams such as data engineering and software development to deploy the data science solutions to production and integrate it with existing IT digital solutions and products
• Exploratory data analysis for extracting business insights from large volume of data using data science toolkits and statistical packages.
• Translate and visualize data into information and insights to discover trends and patterns for solving the business problem and improving the Key Performance Indicators (KPIs)
• Perform data quality assessments and statistical testing to verify data quality and data integrity

Your Qualifications
Required:

• Comprehensive statistical knowledge (regression/classification models, design of experiments, statistical testing etc.) and experience applying it to real-world projects.
• Experience in data mining for large volumes of data, extracting insights and building prediction and system optimization models.
• Experience delivering data science projects from model development to production deployment
• Master’s degree in Applied Mathematics, Statistics, Machine Learning, Electrical Engineering, Computer Science/Information Systems or related fields or MBA with quantitative focus.
• Industrial research and development and advanced data analytics experience.
• Minimum 2 years of full time experience
• Strong knowledge in the application of Machine Learning
• Experience with common data science toolkits, such as SQL, R and/or Python with high proficiency in the use of opensource statistical and machine learning packages (numpy, pandas, scikit-learn, stats tool etc.)

Preferred:

• Experience in deploying predictive or prescriptive data science solutions from any embedded electronic sensor data streams (such as IoT sensors, PLC systems, condition monitoring systems, wearables etc.)
• Deep Learning algorithms (TensorFlow or Equivalent framework), ideally demonstrated by relevant industrial experience

Our Offering
See all of our benefits at: Schaeffler Benefits
As a global company with employees around the world, it is important to us that we treat each other with respect and value all ideas and perspectives. By appreciating our differences, we inspire creativity and drive innovation. In this way, we contribute to sustainable value creation for our stakeholders and society as a whole. Together, we advance how the world moves.
Exciting assignments and outstanding development opportunities await you because we impact the future with innovation. We look forward to your application.
www.schaeffler.com/careers
Schaeffler is an equal employment opportunity / affirmative action employer. All qualified candidates will receive equal employment opportunities and consideration for employment without regard to unlawful consideration of race, color, sex, sexual orientation, gender identity, age, religion, national origin, disability, protected veteran status, or any other status protected by applicable law.
Keywords: Information Technology & Digitalization;
Job Type: Professional
Job Family: Information Technology & Digitalization
Contract Type: Not Applicable
Schedule: Full-Time