4451 وظيفة Engineering Manager Data Science قريبًا مني

Pay Range: $130,000.00 - $160,000.00 / year

Salary offers are based on a wide range of factors including relevant skills, training, experience, education, and, where applicable, certifications obtained. Market and organizational factors are also considered. Successful candidates may be eligible to receive annual performance bonus compensation.

Benefits Information:

We are proud to offer best-in-class benefits and programs to support employees and their families in living healthy, happy lives. Our pay and benefit plans have been designed to promote employee health in all respects – physical, financial, and developmental. Depending on whether it is a part-time or full-time position, some of the benefits offered may include:

• Day 1 Medical, supplemental health, dental & vision for FT employees who work 30+ hours
• Best-in-class well-being programs
• Annual, no-cost health assessment program Blueprint for Wellness®
• healthyMINDS mental health program
• Vacation and Health/Flex Time
• 6 Holidays plus 1 "MyDay" off
• FinFit financial coaching and services
• 401(k) pre-tax and/or Roth IRA with company match up to 5% after 12 months of service
• Employee stock purchase plan
• Life and disability insurance, plus buy-up option
• Flexible Spending Accounts
• Annual incentive plans
• Matching gifts program
• Education assistance through MyQuest for Education
• Career advancement opportunities
• and so much more!

The Senior Manager, Data Science & Business Insights provides leadership for and individual contribution to leverage enterprise data science, advanced analytics, and ML/AI-enabled solutions to provide analytical insights that drive business and operational decision making. This role is accountable for translating complex, cross-functional business challenges into scalable analytical solutions that drive measurable value across Quest Diagnostics.

The Senior Manager partners with senior business, operations, and technology leaders across various domains including Commercial, Finance, Marketing and Operations to advance Quest’s analytics and AI strategy with a primary focus on delivering and representing Operations data science solutions. Success in this role requires strategic and analytic acumen, ability to navigate cross-functionally, and the ability to communicate and sell to functional and BU leaders the value that advanced analytics and data science can bring in business decision making at all levels. The ideal candidate thrives at the intersection of analytics, AI adoption, business & operations strategy, and executive-level engagement, combining a strong analytical and technical foundation with a customer first approach to fuel growth, efficiency, and timely decision making.

This professional will work in a Hybrid capacity, requiring 3 days onsite in our Secaucus headquarters.

Quest Diagnostics honors our service members and encourages veterans to apply.

While we appreciate and value our staffing partners, we do not accept unsolicited resumes from agencies. Quest will not be responsible for paying agency fees for any individual as to whom an agency has sent an unsolicited resume.

Equal Opportunity Employer: Race/Color/Sex/Sexual Orientation/Gender Identity/Religion/National Origin/Disability/Vets or any other legally protected status.

Enterprise Data Science & Advanced Analytics

• Leverage and develop enterprise-scale data science and advanced analytics models and solutions across commercial, marketing, provider, health systems, financial, and operational domains with a focus on delivering operations insights.
• Apply advanced statistical methods, predictive and prescriptive modeling, and machine learning techniques to enable data-driven decision-making and drive business growth and operational efficiencies.
• Ensure analytical solutions are production-ready, scalable, and governed, in alignment with Quest’s data privacy, security, and regulatory requirements.
• Drive adoption of analytics by embedding insights into enterprise workflows and decision processes.

AI, Machine Learning & Intelligent Automation

• Lead the application of machine learning and AI techniques to enterprise use cases, including evaluation and implementation of NLP and Generative AI capabilities.
• Ensure responsible and compliant use of AI technologies in accordance with Quest governance and risk management standards.
• Identify and deliver analytics-driven automation opportunities that improve efficiency and scalability across the enterprise.

Business Partnership & Strategy Execution

• Serve as a strategic analytics and data science partner to senior business leaders across Enterprise and representing the EBA within the Operation function.
• Translate complex analytical insights into clear, actionable recommendations for executive and non-technical audiences.
• Quantify and communicate the business value, impact, and ROI of data science, analytics, ML/AI, and intelligent automation initiatives.
• Contribute to the development and execution of the enterprise data science, analytics, AI/ML, and technology platform roadmap.

Leadership, Talent Development & Delivery

• Lead, mentor, and develop data scientists, analytics engineers, and analysts.
• Establish and reinforce best practices for analytics development, validation, documentation, and knowledge sharing.
• Provide technical leadership and direction across multiple concurrent, cross-functional initiatives
• Operate effectively within a matrixed enterprise environment, influencing outcomes beyond direct reporting lines.
• Trains team members to upskill and enhance their analytics capabilities and drive their adoption of AI-supported tools, automation, processes, and platforms.

Education

• Bachelors or higher in Data Science, Analytics, Engineering, Computer Science, Applied Mathematics, Operations Research, or a related quantitative discipline.

Experience

• 5–8+ years of progressive experience in data science, advanced analytics, or analytics engineering, including leadership and strategy.
• Demonstrated ability to lead complex analytics initiatives from problem definition through production deployment.
• Experience partnering with senior business stakeholders to drive data-informed decisions.
• Experience working with large, complex datasets in regulated or highly operational environments.

Technical Expertise

• Advanced proficiency in Python and/or R for data science, statistical modeling, and machine learning.
• Strong experience with SQL and analytical data modeling.
• Experience with modern data platforms and technologies (e.g., cloud data warehouses, distributed processing frameworks).
• Proficiency with machine learning frameworks and libraries (e.g. PyTorch, Tensorflow, Keras, Scikit-Learn)
• Proficiency with data visualization and BI tools (e.g., Power BI, Tableau, Looker).
• Understanding of ETL/ELT processes, analytics automation, and scalable data pipelines.
• Knowledge of MLOps, model governance, and production AI environments.

Leadership & Professional Skills

• Proven ability to deliver outcomes in a complex, matrixed organization.
• Strong strategic thinking, analytical problem-solving, and execution skills.
• Excellent communication skills with the ability to influence senior leaders.
• Experience managing multiple high-priority initiatives simultaneously.
• Working knowledge of Agile, Scrum, Lean, or similar delivery methodologies.

Preferred Qualifications

• PhD/Graduate-level qualification in Quantitative, Data Science, Engineering field
• Prior experience in healthcare, diagnostics, or life sciences.
• Experience shaping enterprise analytics, data science, or platform standards
• Direct experience designing or operating analytics and AI solutions on Google Cloud Platform (GCP) or other production environment.
• Experience applying ML, NLP, GenAI, and other AI algorithms to solve business-related problems

Role Level Expectations (Senior Manager)

• Leads teams and initiatives with enterprise-wide visibility and material business impact.
• Influences platform strategy, analytics standards, and technology adoption beyond immediate team scope.
• Accountable for delivery quality, adoption, and realized business and operational value.