Senior Data Scientist

Job Description

When you’re part of the team at Thermo Fisher Scientific, you’ll do important work. Surrounded by collaborative colleagues, you’ll have the support and opportunities that only a global leader can give you. Our respected, growing organization has an outstanding strategy for the near term and beyond. Take your place on our strong team, and help us make significant contributions to the world.

Job Overview:

In this role, you will be responsible for using your expertise in data science, statistical modeling, and machine learning to derive actionable insights and solutions for the organization. You will work closely with cross-functional teams to understand business requirements, design analytical solutions, and contribute to data-driven decision-making processes.

Responsibilities:

Data Analysis: Analyze large datasets to identify trends, patterns, and insights. Develop and implement data cleaning and preprocessing techniques. Conduct exploratory data analysis to discover hidden patterns and correlations.

Statistical Modeling: Build and deploy statistical/data science models to tackle business problems. Perform hypothesis testing and develop experiments to validate models. Collaborate with partners to understand model requirements and objectives.

Machine Learning: Develop and implement machine learning algorithms for predictive modeling. Evaluate and fine-tune models for efficient performance. Stay updated on the latest advancements in machine learning and data science.

Data Visualization: Create visually compelling and insightful data visualizations. Communicate findings to both technical and non-technical stakeholders. Use tools like Tableau, Power BI, or others for effective data representation.

Collaboration: Work collaboratively with cross-functional teams, including business analysts, engineers, and other data professionals. Provide mentorship to junior data scientists and contribute to a collaborative work environment.

Project Management: Manage end-to-end data science projects, from problem definition to implementation. Prioritize tasks, meet deadlines, and ensure project work align with business goals.

Continuous Learning: Stay abreast of industry trends, emerging technologies, and standard methodologies in data science. Actively participate in professional development activities and training.

Qualifications:

• Bachelor's or Master's degree in a relevant field (e.g., Computer Science, Statistics, Data Science).
• 5+ years of experience in data science domain.
• Experience of developing a recommendation model will be added advantage.
• Proficiency in programming languages such as Python or R.
• Proficiency of working using cloud platform like Databricks, GCP etc.
• Solid understanding of data manipulation and analysis tools (e.g., Pandas, NumPy).
• Experience with machine learning frameworks (e.g. TensorFlow, PyTorch).
• Superb communication and collaboration skills.
• Strong problem-solving and critical-thinking abilities.

Benefits

• We offer competitive remuneration, annual incentive plan bonus, healthcare, and a range of employee benefits. Thermo Fisher Scientific offers employment with an innovative, forward-thinking organization, and outstanding career and development prospects. We offer an exciting company culture that stands for integrity, intensity, involvement, and innovation!
• Our Mission is to enable our customers to make the world healthier, cleaner and safer. Watch as our colleagues explain 5 reasons to work with us. 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. #StartYourStory at Thermo Fisher Scientific, where diverse experiences, backgrounds and perspectives are valued.

Apply today! http://jobs.thermofisher.com

Thermo Fisher Scientific is an EEO/Affirmative Action Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other legally protected status.

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