Data Scientist

Description

As a Data Scientist in our team, you will work on data science projects across the company with the purpose of solving complex business problems by applying advanced methods including artificial intelligence, machine learning, causal inference, advanced statistics, computer vision, natural language processing and other related techniques.

 

Data Scientists are experienced in delivering successful data science projects in a team and working in collaboration with business partners to develop applications utilizing data for smart decision making. You will also design and build computational models, discovering insights and identifying opportunities using statistical and algorithmic methods as well as data visualization techniques. Turning data into critical information and knowledge, the Data Scientist will manage small projects, potentially including external support and develop and mentor more junior colleagues.

 

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.

 

This role is based out of our Ridgefield, CT campus (2-3 days per week on site).

 

Compensation Data

This position offers a base salary typically between $111,000 by $183,000.  The position may be eligible for a role specific variable or performance based bonus and or other compensation elements.  For an overview of our benefits please click here. 

Duties & Responsibilities

Design and implement end-to end data science projects/ use cases using agile methodologies.

Collaborate with business units to understand and solve problems.

Develop and deploy high-quality, scalable data solutions, collaborating with developers.

Establish the monitoring of data science models in production.

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

Mentor junior colleagues, manage small projects, coach other IT team members on principles and techniques, providing thought leadership.

Promote knowledge exchange within and outside the organization.

Establishing close collaborations with business units to transform towards smart decision making and guide the organization on the strategy of artificial intelligence (AI)/data science.

Why Boehringer Ingelheim?

• Contribute to global projects and collaborate internationally.
• Enjoy a supportive work environment with a focus on work-life balance, diversity, and inclusion.
• Competitive compensation and benefits, 401K, Pension and much more.

Requirements

• Bachelor’s Degree in a quantitative field (e.g., Physics, Mathematics, Computer Science).
• 5+ years of relevant data science experience.
• Proficiency and 2 years’ experience in Python, R, C++, and parallel computing.
• Experience with big data tools (Hadoop, Spark) and scripting languages (PHP, Perl, Bash).
• Unix environment experience
• Expertise in relevant methods and skills such as data wrangling, EDA, data visualization, prototyping, feature engineering, dimensionality reduction, classification methods, regression methods, clustering methods, computer vision methods, time-series analysis, causal inference, NLP.
• Knowledge of ETL processes and various data formats, types of database operations, concepts, architecture, data hygiene /enrichment.
• Knowledge for API usage, web scraping and text processing
• Strong analytical and problem-solving skills.
• First-hand experience of collaboration in an agile software development team
• 2 years of deep analytical problem solving in business or quantitative analytical research.
• Expertise designing, setting up and executing validation and experimentation of data science outcomes in business environments.
• Experience in project management, driving and deliv