- Salary
- $195k – $361k
- Location
- East Hanover, United States of America · Distant Employee - Distant Working Arrangement (DWA) (USA)
- Workplace
- Hybrid, Onsite
- Type
- Full-time
- Department
- IT
- Seniority
- Director
- Experience
- 10+ years
- Source
- Workday
Description
Band
Level 6
Job Description Summary
#LI-HybridThis position plays a vital role in integrating AI-driven solutions across various platforms, fostering collaboration between the US commercial team and the India-based data science team. By championing the exploration of cutting-edge AI technologies, the Director ensures that our strategies are informed by the latest advancements in generative AI and large language models (LLMs). This role will collaborate with other members of the team to create, pilot, and scale AI tools to support broader goals to transform business processes and outcomes.
The ideal location for this role is East Hanover, NJ but a distant working arrangement may be possible in certain states. Distant workers are responsible for the cost of home office expenses and periodic travel/lodging will be determined necessary by hiring manager. For associates working on-site, relocation assistance to be within 50 miles of the site may be available. This position will require 10% travel as defined by the business (domestic and or international).
There are 3 positions available.
Job Description
Key Responsibilities:
Lead the development and deployment of scalable AI solutions, focusing on advanced AI applications across various business units.
Be prepared to engage in hands-on work when necessary to support the team and further our data science initiatives.
Collaborate with cross-functional teams to integrate AI-driven solutions across various platforms and services.
Drive innovation by staying current with advancements in AI, particularly in generative models and LLM technologies.
Champion the exploration and integration of cutting-edge AI technologies, particularly in the field generative AI.
Act as a key liaison between the US commercial team and the India-based data science team.
Stay abreast of state-of-the-art foundation models and other innovative trends in data science and leverage these insights to inform our strategies.
Bring a “can-do” attitude and teamwork and inspire others on culture change.
Acts as an AI role model, championing a culture that embraces cutting-edge AI technologies and encourages experimentation and adoption of best practices
Experience:
Novartis is seeking an individual with proven experience working with machine learning models. They should have a strong ability to support cross-team development of AI programs. A firm commitment to driving continuous improvement in AI solutions, informed by current innovations, is vital to this role.
Essential Requirements:
Advanced degree in Computer Science, Engineering, Statistics, or related field
Minimum of 10 years of experience in data science, with 6 years of experience in the pharmaceutical industry is preferred.
Build and deploy scalable machine learning models using cloud-based services such as AWS and Azure
Strong understanding of deep learning algorithms, foundational/ LLM models, statistics, and recommendation system
Deep knowledge of Large Language Models (LLMs) such as GPT, BERT, Cohere, and their applications in real-world scenarios.
Ability to operate in a hands-on capacity when necessary.
Proficient in programming languages such as Python, Spark, TensorFlow, and PyTorch
Experience with digital channel selection for “next best action”
Excellent problem-solving skills and ability to identify creative solutions to complex problems
Strong ability to effectively communicate and work across different time zones
Novartis Compensation Summary:
The salary for this position is expected to range between $194,600 and $361,400 per year.
The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors.
Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.
US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves.
EEO Statement:
The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. We strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential.
Accessibility and reasonable accommodations
The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or in order to perform the essential functions of a position, please send an e-mail to [email protected] call +1 (877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.
https://www.novartis.com/careers/careers-research/notice-all-applicants-us-job-openings
Salary Range
$194,600.00 - $361,400.00
Skills Desired
Artificial Intelligence (AI), Business Value Creation, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Mentorship, Stakeholder Engagement, Statistical Analysis, Time Series Analysis