Boehringer Ingelheim Jobs

Description

Role located onsite in Fremont, CA.

As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development, and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies' success. We realize that our strength and competitive advantage lie with our people. We support our employees in several ways to foster a healthy working environment, meaningful work, diversity and inclusion, mobility, networking, and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim's high regard for our employees.

The Senior Data Scientist will execute data science projects at US Biopharma Fremont 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 highly experienced in delivering successful data science projects and will work in close collaboration with different business units (e.g., Biopharma sites in Vienna and Biberach) to develop applications which utilize data for smart decision making.

The role will include the responsibility for designing and building computational models, discovering insights, and identifying opportunities using statistical and algorithmic methods (for instance machine learning) as well as data visualization techniques. The Senior Data Scientist will utilize their experience to manage small and medium-sized projects, potentially including external support and to develop and mentor more junior colleagues.

Duties & Responsibilities

Delivering successful data science projects:

• Understands business problems and design end-to-end data science use cases.

• Collaborates across the business to understand data, and business constraints.

• Prioritizes, scopes, and measures the corresponding Key Performance Indicators (KPIs)/ Objectives and Key Results (OKRs) for success.

• Collaborates with developers to implement and deploy scalable solutions.

• Establishes best data operational practices and maintain all compliance requirements.

• Establishes the monitoring of data science models in production.

Achieving high analytical quality of delivered projects:

• Applies strong expertise in data science to design, prototype, and build the next-generation analytics engines and services.

• Generates hypotheses about the underlying mechanics of the business process together with domain experts.

• Identifies, evaluates, and implements the most appropriate algorithm for the specific challenge.

Establishing close collaborations across different departments to transform towards smart data-driven decision making:

• Guides the organization about the business potential and strategy of artificial intelligence (AI)/data science.

• Actively networks on a regular basis with domain experts to better understand the business mechanics that generated the data.

• Quickly develops extensive domain knowledge in various topics.

• Trains and coaches other business and staff on basic data science principles and techniques.

Successful management of communities and partnerships:

• Actively networks on a regular basis with internal and external partners.

• Promotes collaboration and knowledge exchange with other data science teams within and outside the organization.

• Provides thought leadership by researching best practices, conducting experiments, and collaborating with industry leaders.

Requirements

• BS degree, with six-plus (6+) years relevant industry experience.

AND/OR

• MS degree with four-plus (4+) years relevant industry experience.

AND/OR

• PhD degree with two-plus (2+) years relevant industry experience.

• Scientific degree in quantitative discipline such as theoretical physics, mathematics, computer Science, bioinformatics etc.

Technical Skills:

• Deep technical expertise in at least one relevant field.

• Experienced in handling unusual data sets such as unstructured data or big data.

• Broad understanding of current technologies and technological developments including ability to evaluate potential technological benefits for data science projects.

• Five-plus (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.

• Sound knowledge in scripting languages such as PHP, Perl, Bash.

• Experience with Large Language Models and/or mechanistic models is a plus.

Analytical Skills:

• 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.

• 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 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.

Business Skills:

• 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.

• 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).

Eligibility Requirements :

• Must be legally authorized to work in the United States without restriction.

• Must be willing to take a drug test and post-offer physical (if required).

• Must be 18 years of age or older.

Data Scientist II

Requirements

• BS degree, with four-plus (4+) years relevant industry experience.

• AND/OR

• MS degree with two-plus (2+) years relevant industry experience.

• AND/OR

• PhD degree with zero to two (0-2) years relevant industry experience.

• Scientific degree in quantitative discipline such as data science, mathematics, computer science, bioinformatics, etc.

All qualified applicants will receive consideration for employment without regard to a person’s actual or perceived race, including natural hairstyles, hair texture and protective hairstyles; color; creed; religion; national origin; age; ancestry; citizenship status, marital status; gender, gender identity or expression; sexual orientation, mental, physical or intellectual disability, veteran status; pregnancy, childbirth or related medical condition; genetic information (including the refusal to submit to genetic testing) or any other class or characteristic protected by applicable law.