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Sr. Data Scientist (Remote - US)

Work ScheduleFirst Shift (Days)Environmental ConditionsOfficeJob DescriptionAt Thermo Fisher Scientific, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life - enabling our customers to make the world healthier, cleaner and safer. We provide our teams with the resources needed to achieve individual career goals while taking science a step beyond through research, development and delivery of life-changing therapies. With clinical trials conducted in 100+ countries and ongoing development of novel frameworks for clinical research through our PPD clinical research portfolio, our work spans laboratory, digital and decentralized clinical trial services. Your determination to deliver quality and accuracy will improve health outcomes that people and communities depend on – now and in the future.Our Mission is to enable our customers to make the world healthier, cleaner and safer. As one team of 100,000+ colleagues, we share a common set of values - Integrity, Intensity, Innovation and Involvement - working together to accelerate research, solve complex scientific challenges, drive technological innovation and support patients in need.We are seeking a dedicated and experienced Sr. Data Scientist with a focus in Application Development having a solid background in computer science, web development (front and back-end), statistics, machine learning, and leadership skills to join our team. As a Sr. Data Scientist, you will play a crucial role in designing, developing, deploying, and maintaining applications deployed in multiple frameworks to advance operational efficiencies and enhance data volume and integrity for future AI development. If you are passionate about using R/Shiny and Streamlit frameworks to develop advanced statistical and AI/ML application products influencing timelines in bringing therapies to market, we would love to hear from you. Join our dynamic team and make a meaningful impact on our organization's success.Summarized Purpose:Executes advanced analytics modeling based on exploratory data analysis from complex and highdimensional datasets through application of statistics, machine learning, programming, data modeling, simulation, and/or advanced mathematics to recognize patterns, identify opportunities, and generate valuable predictive business insights in support of innovative business decisions. Supports organization leadership through data-driven decision validation and support.Essential Functions:• Effectively collaborates with cross-functional stakeholders to identify questions and business challenges and determine plans of action in order to effectively define, design, and develop machine learning models and algorithms to derive insights into each problem.• Generates and tests hypotheses and analyzes and interprets the results.• Navigates large, complex datasets for data mining, profiling, and curation, and natural language processing (NLP), as well as identifies related data that is fundamental to successfully applying predictive and machine learning techniques.• Designs, develops and programs methods, processes, and software programs to consolidate, cleanse, and analyze unstructured, diverse data sources to recognize patterns, identify opportunities, and generate actionable business insights and solutions.• Designs, develops, and evaluates predictive models and algorithms that lead to optimal value extraction from the data in order to support business process improvements and solve business challenges.• Identifies meaningful insights from large data and metadata sources in support of continuous improvement efforts and business process upgrades through exploratory data analysis.• Effectively communicates and guides stakeholders through the machine learning process; Interprets and communicates findings and solutions from analysis and experiments to a broad audience, including business leadership.Job Complexity:Works on problems of diverse scope where analysis of data requires evaluation of identifiable factors.Job Knowledge:A seasoned, experienced professional with a full understanding of area of specialization; resolves a wide range of issues in creative ways. This job is the fully qualified, career-oriented, journey-level position.Supervision Received:Normally receives little instruction on day-to-day work, general instructions on new assignments. Demonstrates good judgment in selecting methods and techniques for obtaining solutions.Business Relationships:Represents the department as a prime contact on projects. Interacts with internal and external personnel on significant matters often requiring coordination between functional areas. Networks with senior internal and external personnel in own area of expertise.Qualifications:Education and Experience:• Bachelor's degree or equivalent and relevant formal academic / vocational qualification• Previous experience that provides the knowledge, skills, and abilities to perform the job (comparable to 5+ years).• In some cases an equivalency, consisting of a combination of appropriate education, training and/or directly related experience, will be considered sufficient for an individual to meet the requirements of the role.Knowledge, Skills and Abilities:• Strong working knowledge of application of statistics, programming, data modeling, simulation, and advanced mathematics to business questions for data analysis• Demonstrated skills with exploratory data analysis techniques involving structured and unstructured data, machine learning (e.g. decision trees, neural networks, clustering, classification, Bayesian networks), model validation techniques, and data visualization techniques• In depth knowledge in one or more of the following technical areas: Snowflake, AWS EMR, Python, Spark, R, Shiny, jupyter, and associated packages and libraries from numpy, pandas, SciPy or NLTK• Thorough knowledge of and exposure to cloud architectures across NoSQL, lambda functions, kafka, sagemaker, tensorflow, etc.• Proficiency with the following data science approaches: data engineering, pipelining and wrangling tools, data visualization and modeling tools, and mathematical approaches to imperfect data• Substantial knowledge of data management approaches such as relational databases, data schemas, object stores, column stores, triple stores, graph stores, and/or document stores• Proven ability to deliver accurate work products in a cross-functional matrix environment spanning data warehousing, data modeling, and data analytics while managing multiple competing priorities• Sound analytical skills and demonstrated proficiency in developing detailed analysis, models, plan calculations, and tools• Solid executive presence with ability to communicate effectively and influence at all levels• Demonstrated creativity in identifying non-traditional data sources in addition to rigorous application of leading analytic techniquesManagement Role:No management responsibilityWorking Conditions and Environment:• Work is performed in an office environment with exposure to electrical office equipment.• Occasional drives to site locations with occasional travel both domestic and international. Physical Requirements:• Frequently stationary for 6-8 hours per day.• Repetitive hand movement of both hands with the ability to make fast, simple, repeated movements of the fingers, hands, and wrists.• Frequent mobility required.• Occasional crouching, stooping, bending and twisting of upper body and neck.• Light to moderate lifting and carrying (or otherwise moves) objects including luggage and laptop computer with a maximum lift of 15-20 lbs.• Ability to access and use a variety of computer software developed both in-house and off-the-shelf.• Ability to communicate information and ideas so others will understand; with the ability to listen to and understand information and ideas presented through spoken words and sentences.• Frequently interacts with others to obtain or relate information to diverse groups.• Works independently with little guidance or reliance on oral or written instructions and plans work schedules to meet goals. Requires multiple periods of intense concentration.• Performs a wide range of variable tasks as dictated by variable demands and changing conditions with little predictability as to the occurrence. Ability to perform under stress. Ability to multitask.• Regular and consistent attendance.Salary Transparency:This is a salaried role that will also be eligible to receive a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy. Compensation will be initially discussed during the screening period, with actual compensation confirmed in writing at the time of offer.We offer a comprehensive Total Rewards package that our US colleagues and their families can count on, which generally include:• A choice of national medical and dental plans, and a national vision plan• A wellness program, and valuable health incentive opportunities for company contributions to a Health Reimbursement Accounts (HSAs) or Health Savings Account (HSA)•Tax-advantaged savings and spending accounts and commuter benefits• Employee assistance programs• At least 120 hours paid time off (PTO). 10 paid holidays annually, paid parental leave (3 weeks for bonding and 8 weeks for caregiver leave), accident and life insurance, short- and long-term disability, and volunteer rime off in accordance with company policy.• Retirement and savings programs, such as our competitive 401(k) U.S. retirement savings planAccessibility/Disability AccessWe will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.EEO & Affirmative ActionThermo Fisher Scientific is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, creed, religion, color, national or ethnic origin, citizenship, sex, sexual orientation, gender identity and expression, genetic information, veteran status, age or disability status.
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What You Should Know About Sr. Data Scientist (Remote - US), Thermo Fisher Scientific

At Thermo Fisher Scientific, we are thrilled to announce an opening for a Sr. Data Scientist (Remote - US) who is passionate about making a global impact through data. This role is perfect for someone who has a robust background in application development, statistics, machine learning, and web development. You’ll be at the forefront of advancing operational efficiencies and enhancing data integrity, driving our mission of making the world healthier, cleaner, and safer. As a Sr. Data Scientist, you'll collaborate with cross-functional teams, utilizing your skills in R/Shiny and Streamlit to develop advanced applications that will influence the delivery of life-changing therapies. With your analytical expertise, you'll navigate complex datasets, design predictive models, and provide actionable insights that will help shape the organization's decisions. If you're a natural problem-solver with a knack for statistical analysis and a strong desire to innovate, we would love to hear from you. Join our dynamic and diverse team where your contributions will directly support improving health outcomes for communities around the world.

Frequently Asked Questions (FAQs) for Sr. Data Scientist (Remote - US) Role at Thermo Fisher Scientific
What are the key responsibilities of the Sr. Data Scientist at Thermo Fisher Scientific?

As a Sr. Data Scientist at Thermo Fisher Scientific, your main responsibilities include collaborating with stakeholders to identify business challenges, developing machine learning models, and generating actionable insights from complex data sets. You will navigate large datasets, design applications, and communicate findings to diverse audiences, all while ensuring quality and accuracy in data-related processes.

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What qualifications are required to apply for the Sr. Data Scientist position at Thermo Fisher Scientific?

To apply for the Sr. Data Scientist position at Thermo Fisher Scientific, candidates should have a Bachelor's degree in a relevant field and at least 5 years of experience in data science or a related area. Strong knowledge of statistics, machine learning techniques, and proficiency in programming languages such as Python and R are essential for this role.

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How does the Sr. Data Scientist contribute to the mission of Thermo Fisher Scientific?

The Sr. Data Scientist plays a crucial role in driving Thermo Fisher Scientific's mission by transforming raw data into valuable insights that improve health outcomes. By designing predictive models and advanced applications, you will influence decision-making processes that facilitate the development of life-changing therapies, ultimately impacting patient care on a global scale.

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What programming languages and tools should a candidate be proficient in for the Sr. Data Scientist role at Thermo Fisher Scientific?

Candidates for the Sr. Data Scientist role at Thermo Fisher Scientific should be proficient in programming languages such as Python and R, as well as frameworks like Streamlit and R/Shiny. Familiarity with data tools and platforms such as AWS EMR, Snowflake, and data visualization libraries is essential for success in this position.

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What is the working environment like for a Sr. Data Scientist at Thermo Fisher Scientific?

The working environment for a Sr. Data Scientist at Thermo Fisher Scientific is primarily office-based but offers remote flexibility for U.S. applicants. The role involves collaboration across various teams, and you will often engage in problem-solving discussions to guide data-driven decisions in a supportive and innovative atmosphere.

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Common Interview Questions for Sr. Data Scientist (Remote - US)
Can you explain your experience with machine learning algorithms?

When answering this question, highlight your experience with different types of machine learning algorithms such as decision trees, neural networks, and clustering methods. Discuss specific projects where you've applied these techniques, the outcomes, and how they contributed to data-driven decisions.

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How do you handle large datasets in your data analysis projects?

Explain your approach to managing large datasets, including data cleaning, preprocessing, and the tools you use for analysis. Mention any specific software or programming languages you've utilized, such as Python libraries or SQL databases, to efficiently handle and analyze big data.

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Describe a challenging data problem you encountered and how you solved it.

In your response, provide a detailed account of a specific data challenge, including the context, the techniques you employed, and the results achieved. Emphasize your problem-solving skills and the impact your solution had on the project or organization.

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What methodologies do you employ for exploratory data analysis?

Discuss your methodologies for exploratory data analysis (EDA), like data profiling techniques, visualization tools, and statistical measures you apply to uncover patterns and insights in data. Providing concrete examples will strengthen your response.

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How do you ensure data quality in your models?

Talk about techniques you've implemented to ensure data quality, such as validation checks, data cleaning processes, and model evaluation metrics. Stress the importance of accuracy and reliability in the data modeling process.

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What experience do you have with data visualization tools?

Mention any data visualization tools and libraries you're proficient in, such as Tableau, Python's Matplotlib, or R's ggplot. Describe how you've used data visualization to communicate complex results to stakeholders effectively.

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Can you share an example of a project where you utilized R or Python for data analysis?

Provide a specific example of a project that involved using R or Python for data analysis, detailing the problem, your approach using the programming language, the outcomes you achieved, and any challenges you faced during the project.

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How do you stay updated with the latest trends in data science?

Describe various ways you keep abreast of the latest data science trends, including attending conferences, participating in webinars, following industry leaders on social media, and engaging with online courses. Show your enthusiasm for continuous learning in the field.

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How do you approach teamwork and cross-functional collaboration?

In your response, highlight your experiences working in cross-functional teams. Discuss your communication strategies, how you present findings to non-technical stakeholders, and how you collaborate effectively to drive projects to success.

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What are your long-term career goals as a Sr. Data Scientist?

Discuss your long-term career aspirations while tying them back to the mission and values of Thermo Fisher Scientific. Talk about how you want to leverage your skills in data science to drive innovations that can improve health outcomes and support the mission of the organization.

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Our Mission is to enable our customers to make the world healthier, cleaner and safer. Whether our customers are accelerating life sciences research, solving complex analytical challenges, improving patient diagnostics and therapies or increasing ...

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Full-time, remote
DATE POSTED
December 3, 2024

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