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Jacobs Entry Level Data Analyst in Boston, Massachusetts

Jacobs is currently looking for an Entry Level Data Analyst to work within our Life Sciences market in the United States. This candidate will work with the Engineering and Construction Management teams to identify data sources, gather data and process and validate the data to produce insightful reports and dashboards which will highlight opportunities within the business and help to determine the root causes of problems to be addressed. The data analyst shall be required to provide recommendations on improvements to data capture and produce guidance documentation on best practices on data capture and reporting requirements. We will rely on you, working as a member of our multi-discipline teams, to build data driven solutions that positively impact our communities.

In this role, you should be highly analytical with a knack for analysis, math, and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for developing tools and systems that improve the day to day working lives of our employees and optimize their ability to deliver to our clients.

Typical activities will include:

· Collaborate with Jacobs’ project team members, project leadership, subject matter experts and solution development teams

· Propose solutions and strategies to business challenges

· Identify data sources and automate collection processes

· Undertake preprocessing of structured and unstructured data

· Analyze large amounts of information to discover trends and patterns

· Perform analytics and maintenance of large database across multiple departments

· Carry out issue identification and analysis techniques, such as pattern analysis and root cause analysis, to help identify issues and propose solutions

· Work close to stakeholders gathering requirements, performing analysis and delivering complex analysis to supply data driven insight to support strategic business decision-making

· Develop best practice documentation for the capture, validation and analysis of data across the business.

· Build predictive models and machine-learning algorithms

· Combine models through ensemble modeling

· Present information using data visualization techniques

· Prepare documentation explaining results

Required Qualifications

· BS/BA in Computer Science, Engineering, Mathematics or relevant field; graduate degree or higher in Data Science or other quantitative field is preferred

· 0-2 years of work experience as a Data Scientist or Data Analyst

· Strong math skills (i.e., statistics, algebra)

· Advanced Excel skills using formulas and Pivot tables for data analysis

· Firm understanding of cloud platforms like Azure or AWS

· Knowledge and experience in Python, R, and SQL; familiarity or passion to learn JavaScript, HTML5, CSS, C#, and/or C++; GitHub and Azure DevOps

· Experience using business intelligence tools (i.e., Power BI, Tableau) and data frameworks

· Knowledge of different modelling and data mining techniques

Preferred Qualifications

· Experience in data mining

· Understanding of machine-learning workflows, data management, technology stacks

· Analytical mind and business acumen

· Problem-solving aptitude

· Excellent communication and presentation skills

· Works well both independently and in teams

Jacobs is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, religion, creed, color, national origin, ancestry, sex (including pregnancy, childbirth, breastfeeding, or medical conditions related to pregnancy, childbirth, or breastfeeding), age, medical condition, marital or domestic partner status, sexual orientation, gender, gender identity, gender expression and transgender status, mental disability or physical disability, genetic information, military or veteran status, citizenship, low-income status or any other status or characteristic protected by applicable law. Learn more about your rights under Federal EEO laws and supplemental language.

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