Location: Weston, Massachusetts, United States
Requisition Number: 1008
Position Title: Data Scientist_G01
Bring Big Data to Life!
The Data Scientist at Monster Worldwide in our Weston, MA Headquarters, will solve complex business problems using advanced statistical methods. The role will be able to work independently or guide junior Data Scientists on various Data Science, Automated ML and Data Engineering tasks. The role will execute a Data Science project from end to end, from participating in stakeholder meetings and defining business problems, to delivery of analytic outputs and implementation of findings.
Our Data Science Team delivers analytic solutions across a wide variety of Monster applications. We build and inferential and predictive models, including machine learning algorithms and AI, we process, integrate and manipulate big data with distributed systems and varied data pipelines and we synthesize results and translate findings into compelling stories that resonate with stakeholders.
- Use statistical, mathematical, predictive modelling capabilities to ask the right questions and find the right answers.
- Communicate findings, orally and visually.
- Has knowledge of Big Data engineering and data manipulation methods and tools and can perform these tasks independently AND/ OR has knowledge of advanced statistical techniques and tools and can perform these tasks independently
- Writes efficient, organized, shareable code, develops ETL processes and functions to automate tasks or produce analytics/ data products
- Oversees work and provides coaching to junior team members; provides training to new employees
- Engages with business stakeholders and translates business problems into analytics projects; summarizes, visualizes and communicates statistical/ML processes and results for stakeholders; helps translate analytics outputs into actionable insights
Knowledge and Skills
- Minimum 1 year of relevant experience, preferable with a focus on Big Data Analytics
- Experience building ETL pipelines for cloud-based projects from initial inception to production
- Experience implementing a range of statistical or machine learning methods, from basic descriptive statistics, hypothesis testing and feature transformation to complex dimension reduction, supervised or unsupervised learning, and model turning and validation
- Proficiency in Python and/or R, SQL
- Familiarity with Linux and/or Spark preferred; knowledge of distributed computing would be a plus
- Demonstrated ability to communicate complex technical concepts to non-technical audiences
- Demonstrated passion for problem solving; ability to perform tasks independently; comfortable with dealing with complex and ambiguous business problems
- Competitive salary with bonuses
- Flexible hours
- Generous vacation policy
- Medical, dental and vision insurance
- Lots of room to grow and learn new things
- Very competitive 401k matching
Monster is a global leader in connecting people to jobs, wherever they are. For more than 20 years, Monster has helped people improve their lives with better jobs, and employers find the best talent. Today, the company offers services in more than 40 countries, providing some of the broadest, most sophisticated job seeking, career management, recruitment and talent management capabilities.
Monster continues its pioneering work of transforming the recruiting industry with advanced technology using intelligent digital, social and mobile solutions, including our flagship website monster.com® and a vast array of products and services.
Monster is committed to fostering an inclusive work environment through a culture of diversity, equity, safety, and belonging. Our goal is to make work a happy and productive place for all through transparency and accountability at all levels of our organization.
If there’s an accommodation you need or prefer as part of your application, or if you have some feedback for us on ways we can make our process more accessible for all, please send us an email at email@example.com or call 1-800-MONSTER and let us know how we can help!
Please do not direct any general employment related questions to this email and/or phone number. Please note that only those inquiries concerning a request for reasonable accommodations will be responded to from this email address and/or phone number.
Monster is an Equal Opportunity and Affirmative Action Employer committed to creating a diverse environment. Qualified applicants will be considered for employment regardless of Race, Religion, Color, National Origin, Citizenship, Sex, Sexual Orientation, Gender Identity, Age, Disability, Ancestry, Veteran Status, Genetic Information, Service in the Uniformed Services or any other classification protected by law.
Community / Marketing Title: Data Scientist
Monster (Randstad Group) is the worldwide leader in successfully connecting people to job opportunities. From the web, to mobile, to social, we help companies find people with customized solutions and we use the world's most advanced technology to match the right people to the right job.
We've made it our mission to help companies find better candidates. And nobody brings more cutting-edge tools to help them do just that than Monster. Whatever their needs are, we have the products and technologies to build a bespoke solution for our clients, to help them find #TheRightFit.
Innovation is the heart of our success... and our future. We're changing the way people think about work, and we're helping them improve their lives and their work performance with new technology, tools and training.
What makes Monster great…
Monster is synonymous with innovation; we are passionate about bringing great people and great companies together. In fact, we are obsessive about it – it’s what we do every day. We believe that the work that we do has a noble purpose... Making people’s lives better.
At Monster, we let people breath, giving everyone the opportunity to shape their destiny and provide the development support that allows them to do so.
Find out more about Working at Monster here: https://www.monster.com/about/working-here/
Location_formattedLocationLong: Weston, Massachusetts US
CountryEEOText_Description: US EEO Verbiage