上海勃林格殷格翰药业有限公司新闻资讯

Talent@Boehringer Ingelheim

About Corporate Functions
Corporate functions staff are the backbone of the company: talented, conscientious professionals who think outside the box and get things done. We set Boehringer Ingelheim's strategic compass to sustainable, reliable, innovative and customer-oriented. Internally, we ensure we have the employees' company needs covered so they can develop and grow here successfully. We also offer intelligent solutions and systems, overlook processes, investments and budgets, provide guidance to our businesses, and communicate to our internal and external stakeholders. We are proud of being a strategic partner to our business functions.

Job Responsibilities
The Senior Data Scientist will execute data science projects across the company with the purpose of solving non-routine business problems by applying advanced methods including artificial intelligence, machine learning, causal inference, advanced statistics, natural language processing and other related techniques.
The Senior Data Scientist is experienced in delivering successful data science projects and will work in close collaboration with all business units to develop applications which utilize data for smart decision making. Explicitly, the role will include the responsibility for designing and building computational models, discovering insights and identifying opportunities through the use of statistical and algorithmic methods (for instance machine learning) as well as data visualization techniques.
Data Scientists work closely with business units and IT to turn data into critical information and knowledge. The Senior Data Scientist will utilize his/her experience to manage small and medium-sized projects, potentially including external support and to develop and mentor more junior colleagues.
-Delivering successful data science projects:
-Understand business problems and design end-to-end data science use cases
-Collaborate across the business to understand data, IT and business constraints
-Prioritize, scope and measure the corresponding Key Performance Indicators (KPIs)/ Objectives and Key Results (OKRs) for success
-Collaborate with developers to implement and deploy scalable solutions
-Establish best data operational practices and maintain all compliance requirements
-Establish the monitoring of data science models in production
-Lead agile approach to initiatives and launches
-Achieving high analytical quality of delivered projects:Apply strong expertise in data science to design, prototype, and build the next-generation analytics engines and services
-Generate hypotheses about the underlying mechanics of the business process together with domain experts
-Identify, evaluate and implement the most appropriate algorithm for the specific challenge
-Establishing close collaborations with business units to transform towards smart decision making:Guide the organization about the business potential and strategy of artificial intelligence (AI)/data science
-Actively network on a regular basis with domain experts to better understand the business mechanics that generated the data
-Quickly develop extensive domain knowledge in various topics
-Train and coach other business and IT staff on basic data science principles and techniques
-Successful management of communities and partnerships: Actively network on a regular basis with internal and external partners
-Promote collaboration and knowledge exchange with other data science teams within and outside the organization 
-Provide thought leadership by researching best practices, conducting experiments, and collaborating with industry leaders

Qualifications
-Education/Degree Requirements: Master’s degree or above, advanced scientific degree desirable, e.g. PhD, MD
-Major: Theoretical physics, mathematics, computer science, bioinformatics, etc. or related
-Language skills & proficiency: English working proficiency and communication skills (verbal and written)
-Required capabilities (skills, experience, competencies):
-5+ years of relevant work experience in data science
-First-hand experience of the intense collaboration in an agile software development team
-Technical Skills:
-Deep technical expertise in at least one relevant field
-Experienced in parallel computing
-Experienced in handling unusual data sets such as unstructured data or big data (MapReduce approaches, HDFS, Hadoop architectures, Pig, Spark)
-High level of expertise in understanding of platform and infrastructure architectures and most common interface types
-Broad understanding of current technologies and technological developments including ability to evaluate potential technological benefits for data science projects
-5+ years experience in relevant computing languages such as R, Python and C++
-Experienced in handling unix environments
-Understanding of ETL processes and experience with various data formats
-Experienced in handling various types of data bases including data base operations and understanding of data base concepts and architectures
-Well-developed understanding of data hygiene as well as data enrichment
-Experienced in handling data bases including ability to run queries
-Basic understanding of web scraping and text processing
-Sound knowledge in scripting languages such as PHP, Perl, Bash
-Strong intrinsic appetite to develop technical skills
-Analytical Skills:
-Self-driven oversight of relevant analytical fields and analytical as well as technological developments
-Ability to rapidly develop analytical problem-solving approaches to complex problems, including external constraints such as resource limitations, feasibility topics, consumption by business, change management aspects, etc.
-5+ years of deep analytical problem solving in business environments or quantitative analytical research
-High level of expertise to design, set up and execute validation and experimentation of data science outcomes in business and market environments
-High level of expertise to extract and develop deep analytical insights from complex data sets including identification of patterns
-Demonstrated ability to solve challenging and prior un-solved questions
-High level of expertise in relevant methods and skills such as machine learning, advanced statistics, algebra, data visualization, artificial intelligence, natural language processing, classification methods, feature extraction, dimensionality reduction, data handling algorithms, regression methods, time-series analysis, predictive modelling, causal inference methods, Bayesian networks, Markov random fields, text analysis, etc.
-Strong self-driven ability to develop analytical expertise further through data science project work and close monitoring of academic and industrial developments of relevant fields.
-Ability to develop, evaluate and apply scientific problem-solving approaches to challenging analytical problems
-Ability to work autonomously
-Strong intrinsic intellectual curiosity and well-established mindset for ongoing development of analytical skills
-Business Skills:
-Firm expertise and established experience in project management
-Demonstrated ability to successfully drive and deliver data science projects
-Well-developed ability to engage with business users and to communicate effectively with different project and business stakeholders
-Ability to successfully manage different and potentially conflicting interests of various stakeholders in the framework of data science projects
-High expertise in change management demonstrated through several projects that involved a high degree of business transformation
-Demonstrated ability to build close partnerships with business owners
-Demonstrated ability to quickly understand and adapt to new challenging business questions
-Well-established ability to communicate effectively with various business stakeholders including senior management levels
-Firm ability to quickly evaluate business cases
-Ability for out-of-the box thinking and innovative problem solving in business contexts including an entrepreneurial mindset
-Strong written and verbal communication skills
-Ability to build relationships with business partners, operational managers and colleagues
-Ability to handle multiple priorities under set deadlines
-Ability to constantly adapt to a fast-paced multidisciplinary changing environment (e.g. with regards to new data types or changes in competitive landscape)
-Actively contributes to the data science community
-Other Skills:
-Expert knowledge of state-of-the-art agile principles and practices for software product development and delivery
-Initiates and drives activities without guidance
-Entrepreneurial and agile mindset / out-of-the-box thinking
-Fluent in English (written and verbal)
-Pharma experience beneficial but not required