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

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.