Companies Hiring Data Scientists
Here’s a list of companies currently hiring data scientists in Massachusetts with brief requirements and links to their career pages:
Wayfair
Requirements:
- Bachelor’s/Master’s in Data Science, Computer Science, or a related field.
- Experience with Python, R, SQL, and data visualization tools.
- Strong knowledge of machine learning models.
Apply Here: Careers
HubSpot
Requirements:
- Experience in data analytics, machine learning, and data engineering.
- Proficiency in Python and SQL.
- Excellent communication skills.
Apply Here: Careers
Amazon (Cambridge Office)
Requirements:
- Master’s/Ph.D. in Data Science or a related discipline.
- Experience in deep learning frameworks like TensorFlow.
- Ability to work with large-scale data.
Apply Here: Careers
IBM
Requirements:
- Bachelor’s or higher in a technical field.
- Familiarity with machine learning and deep learning.
- Strong programming and data analysis skills.
Apply Here: Careers
Biogen
Requirements:
- Advanced degree in Statistics, Computer Science, or related field.
- Experience in data management and statistical analysis.
- Understanding of healthcare data.
Apply Here: Careers
Vertex Pharmaceuticals
Requirements:
- Degree in Data Science, Statistics, or related field.
- Proficiency with data analysis tools.
- Experience with healthcare datasets.
Apply Here: Careers
Thermo Fisher Scientific
Requirements:
- Bachelor’s in Computer Science, Statistics, or a related field.
- Knowledge of machine learning algorithms.
- Strong programming and data management skills.
Apply Here: Careers
Takeda Pharmaceuticals
Requirements:
- Master’s or higher in Data Science or related field.
- Experience in data analysis, machine learning, and statistics.
- Familiarity with clinical datasets.
Apply Here: Careers
Akamai Technologies
Requirements:
- Advanced degree in Data Science, Computer Science, or similar field.
- Experience in big data tools and data visualization.
- Strong communication and teamwork skills.
Apply Here: Careers
Deloitte
Requirements:
- Bachelor’s/Master’s in a quantitative field.
- Experience with predictive analytics.
- Understanding of business processes.
Apply Here: Careers
Liberty Mutual
Requirements:
- Advanced degree in Data Science, Computer Science, or related field.
- Familiarity with data mining and statistical analysis.
- Knowledge of machine learning and AI.
Apply Here: Careers
Raytheon Technologies
Requirements:
- Advanced degree in Data Science or relevant field.
- Experience in AI and machine learning.
- Knowledge of big data tools and methodologies.
Apply Here: Careers
MassMutual
Requirements:
- Bachelor’s/Master’s in Data Science or a similar field.
- Experience in programming languages (Python, R, etc.).
- Ability to analyze and visualize data effectively.
Apply Here: Careers
Fidelity Investments
Requirements:
- Master’s/Ph.D. in a quantitative field.
- Strong programming skills (Python, R, SQL).
- Experience with financial data analysis.
Apply Here: Careers
Boston Consulting Group
Requirements:
- Bachelor’s/Master’s in Computer Science or relevant field.
- Experience with machine learning, NLP, and data analytics.
- Strong analytical and communication skills.
Apply Here: Careers
Blue Cross Blue Shield of Massachusetts
Requirements:
- Advanced degree in Data Science, Statistics, or related field.
- Experience in healthcare data analysis.
- Knowledge of predictive analytics and AI.
Apply Here: Careers
Pfizer
Requirements:
- Advanced degree in Statistics, Data Science, or related field.
- Experience with clinical trial data.
- Strong programming and statistical skills.
Apply Here: Careers
Nokia (Bell Labs)
Requirements:
- Master’s/Ph.D. in a quantitative field.
- Knowledge of big data tools and techniques.
- Experience with predictive modeling.
Apply Here: Careers
Schneider Electric
Requirements:
- Advanced degree in Data Science, Statistics, or related field.
- Experience with machine learning models and AI.
- Strong statistical analysis and programming skills.
Apply Here: Careers
MITRE
Requirements:
- Bachelor’s/Master’s in Data Science or similar field.
- Proficiency in Python, R, and data visualization tools.
- Familiarity with government data analysis.
Apply Here: Careers
Amgen
Requirements:
- Master’s/Ph.D. in Data Science or relevant field.
- Experience in biostatistics and healthcare data analysis.
- Strong programming skills.
Apply Here: Careers
Ginkgo Bioworks
Requirements:
- Bachelor’s/Master’s in a quantitative field.
- Familiarity with genomic data analysis.
- Proficiency in Python and R.
Apply Here: Careers
Drift
Requirements:
- Bachelor’s in Data Science or relevant field.
- Experience in machine learning and data visualization.
- Strong knowledge of data warehousing tools.
Apply Here: Careers
MathWorks
Requirements:
- Advanced degree in Data Science, Computer Science, or similar field.
- Proficiency with MATLAB and statistical analysis tools.
- Strong programming skills.
Apply Here: Careers
Dell Technologies
Requirements:
- Master’s/Ph.D. in Data Science, Computer Science, or similar.
- Experience with machine learning and data visualization.
- Proficiency in Python, R, and SQL.
Apply Here: Careers
Data Science Jobs in Massachusetts
In the rapidly evolving landscape of technology and big data, Massachusetts has become a prominent hub for data science professionals. Data scientists in this region are pivotal in transforming vast amounts of raw data into actionable insights that drive strategic decisions and innovations across various industries including healthcare, finance, technology, and bio-pharmaceuticals.
Role and Responsibilities of Data Scientists in Massachusetts:
1. Data Analysis and Management:
- Collect, clean, and manage data from diverse sources.
- Ensure data quality and accuracy for analytical processes.
2. Model Development and Machine Learning:
- Develop predictive models and machine-learning algorithms.
- Apply statistical analysis to derive patterns and solutions from data.
3. Data Visualization and Reporting:
- Create visual representations of data to communicate findings effectively.
- Generate reports and dashboards for stakeholders to facilitate decision-making.
4. Cross-functional Collaboration:
- Work closely with different departments (e.g., IT, marketing, operations) to understand business needs and objectives.
- Provide data-driven insights and recommendations to enhance organizational performance.
5. Innovative Solutions and Strategies:
- Innovate and implement new data methodologies and tools for continuous improvement.
- Stay updated with the latest trends and technologies in data science to keep the organization at the forefront of the industry.
6. Ethical Data Usage:
- Uphold ethical standards in data handling and analysis.
- Ensure privacy and security compliance according to industry regulations.
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