Senior Data Scientist Manager

Quest Diagnostics   •  

Secaucus, NJ

Industry: Healthcare


8 - 10 years

Posted 176 days ago

This job is no longer available.

Quest’s Consumer Technologies and Digital Solutions is a quickly growing organization responsible for collaborating across Quest’s three focus areas of General Diagnostics, Advanced Diagnostics and Diagnostic Services to develop and execute digital strategies, delivering cutting-edge, best-in-class products, services and personalized solutions that offer a superior digital consumer experience.


In this role, you will be responsible for building and deepening a holistic view of Quest’s Consumers through data and analytics and applying those insights to inform the development and growth of incredible digital services, content and experiences for our consumers.


We are looking for a data scientist to serve at the intersection of data science and key business partners. This role will focus on deep diving into a broad variety of initiatives around consumer analytics, segmentation, and targeting. It will require a multidisciplinary blend of statistics, technology, and business strategy, all applied in tandem to discover key insights in the data.


The role will involve everything from investigative analysis to scope out new projects, developing algorithmic frameworks and executing on projects, and interacting with key stakeholders to understand needs; develop segmentation and communicates the characteristics of each segment to the broader team for the purposes of segment specific targeting and messaging. Collaborating with our marketing partners, you will track and analyze campaign performance against KPIs and provide evaluation and optimization recommendations accordingly.


Job responsibilities:


As a successful data scientist on the Consumer Technologies and Digital Solutions team, you will need to understand the meanings of data in the context of education, customer acquisition and conversion. You will expose and measure current user behavior. You will identify specific and actionable opportunities to solve existing business problems by collaborating with engineering and business teams for future innovation. You need to be a sophisticated user of advanced data extraction and transformation tools (e.g. Spark, Python, SQL), but will need to understand the source data and be able to synthesize it down to a form suitable for answering specific business questions, machine learning and econometric modeling. You will also need to be an expert at communicating insights and recommendations to audiences of varying levels of technical sophistication.


Specific responsibilities:

  • Develop models that help us understand and describe our customers, e.g. learning how to extract deep interests and tendencies from event streams.

  • Serve as a partner to key business partner teams to understand needs and conduct analyses that will help determine strategy.

  • Create integrated views and segments based on data from multiple sources to influence business designs.

  • Understand and apply machine learning and statistical models to generate deep insight and discover effective solutions to challenging problems.

  • Deliver presentations to business stakeholders that tell cohesive, logistical stories using data.

  • Reframe business objectives as machine learning tasks that can deliver actionable insights, accurate predictions, and effective optimization. 

  • Implement and execute machine learning research with reliability and reproducibility. 

  • Communicate results and impact to business stakeholders. 

  • Turn models into data products, collaborate with engineering teams, and integrate into process throughout Quest Diagnostics.

  • Drive continuous process optimization by measuring impact, discovering efficiencies, and making recommendations.

  • Define meaningful client clusters within each market segment, articulate clear value proposition, build business cases and ROI analysis to attack client clusters, organize for client cluster marketing and provide insight for sales campaigns.

  • Document user-experience research to improve ease-of-use and customer satisfaction.


     Hypothesize and Model

  • Design, size, and analyze field experiments at scale.

  • Create novel and tractable datasets from big data.

  • Retrieve, synthesize, and present critical data in a format that is immediately useful to answering specific questions or improving system performance.

  • Analyze historical data to identify trends and support decision making.

  • Provide requirements to develop analytic capabilities, platforms, and pipelines.


    Investigate and Enlighten

  • Formalize assumptions about how Quests Consumer Technologies and Digital Solutions are expected to perform, create statistical definition of the outlier, and develop methods to systematically identify these outliers. Work out why such examples are outliers and define if any actions needed.

  • Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes. 


    Resolve and Recommend

  • Build decision-making models and propose solution for the business problem you defined

  •  Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.

  • Utilize code (python or another object oriented language) for data analyzing and modeling algorithm

To qualify the ideal candidate will have the following skills and experience:

  • Demonstration of predictive modeling, hypothesis testing, and rapid prototyping in machine learning or data science

  • Demonstration of performance improvement or process redesign        

  • Experience in neural network frameworks and modeling

  • Experience in natural language processing

  • Previous work related or research experience in algorithm design or analytics related to operational or business problems

  • Experience working with large datasets in SQL or NoSQL databases

  • Proficiency in data-science related languages and packages (python, R, Tensorflow, etc.)

  • Proficient in data analytics and engineering, able to clean, transform, and merge data

  • Strong background in statistics methodology

  • 2+ years of experience with open source machine learning or statistical analysis tools. Familiarity with experimental design a plus.

  • Ability to communicate complex ideas in data science to relevant stakeholders.

  • Data engineering experience, including SQL and manipulating large structured or unstructured datasets for analysis.

  • Preferred: Experience with building consumer-facing data products.

  • Preferred: Experience working with unstructured data and Natural Language Processing

  • Statistics, Applied Mathematics, Operation Research, Economics or a related quantitative bachelor or masterdegree.

  • At least 2 years of experience with data querying languages (e.g. SQL), scriptinglanguages (e.g. Python), or statistical/mathematical software (e.g. R, Stata, Matlab).

  • At least 1 year industry or academic experience articulating business questions and using quantitative techniques to arrive at a solution using available data

Technical Qualifications:

  • BA/BS/MS or PhD in CS, statistics, applied math, physics, or other quantitative discipline

  • 7+ years of experience in a corporate, start-up, or research environment

  • 3+ years of experience in a role developing predictive or explanatory models

  • Experience with at least one production-quality programming language (e.g. Python, C++)

  • Experience with customer lifetime value and segmentation algorithms a plus

  • Experience working in a production environment including best practice tools (e.g. cloud architecture, version control)

  • Experience with R a plus                 

Non-Technical Qualifications:

  • Unwavering commitment to Quest Diagnostic’s vision of Empowering better health with diagnosic insights.

  • Desire to join the world’s most exciting healthcare company at a moment in history when the importance of learning from our data is transforming every aspect of healthcare.

  • Excellent analytical and problem-solving skills

  • Strong oral and written communication skills

  • A passion for empirical research and for answering hard questions with data.

  • Proven record of solving challenging problems.

  • Eagerness to collaborate with both technical and non-technical colleagues in product management, marketing, and executive leadership groups.

  • Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick effective solutions as appropriate.  

Preferred Qualifications:

  • Experience processing, filtering, and presenting large quantities (Millions to Billions of rows) of data

  • Experience designing experiments, and ability to infer causal relationships

  • Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment

  • Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences

  • Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment

  • Experience in e-commerce or with search engines is a plus.