Data Scientist

As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
The Data Scientist is part of Welocalize’s Analytics Solutions team, reports to the Data Analytics/BI Leader, and works closely with the head of Data Strategy & Operations. The purpose of this important role is to add advanced Data Science & Machine Learning expertise to the data analytics/BI function, in order to enable the organization to take full advantage of the robust and extensive data ecosystem developed over the past five years; and to help the lead the organization in converting these data assets into improved performance and business value.
This role requires advanced technical competency—robust “hard skills”—but also practical business acumen and an aptitude for direct engagement with business stakeholders. This individual’s most important objectives will require them to develop a working understanding of the way the business works, what the key stakeholders do, and what their objectives are—and use that knowledge to inform the way that the individual’s technical capabilities are utilized.

Responsibilities

• Provide the necessary machine learning/data science expertise, and collaborate with data analysts and data engineers, so that the Analytics Solutions team can:
• Construct, support, and continuously refine our BI data systems;
• Deploy analytical approaches and tools to support business stakeholders with cutting edge business intelligence and data visualizations;
• Leverage the organization’s data assets to develop, maintain, and support the implementation of predictive models that improve business performance in areas such as on-time delivery (OTD), quality performance, and other TBD items.
• Maintain familiarity and stay up-to-date on state-of-the-art machine learning/data science approaches applicable to the role.
• Engage directly with business stakeholders across the organization to cultivate a working knowledge and familiarity with the realities of the business, problems to be solved, and opportunities to add value through data; leverage this knowledge to help the team turn analytical models into practical, value-added solutions.
• Collaborate with product & development teams when and as appropriate to facilitate the deployment of predictive models into business-facing work surfaces and systems.
• Contribute expertise, problem-solving capability, thought leadership, and supplementary bandwidth to ongoing efforts of the Analytics Solutions team, including the maintenance and ongoing development of Data Warehouse, its connection to various other data systems & assets, and ensuring the responsiveness of our BI reporting systems to the evolving needs of the business.
• Apply a diverse set of tactics such as statistics, quantitative reasoning, and machine learning; discerning where simple analytics solutions (e.g. a quick visualization) are preferable to complex solutions (e.g. machine learning).
• Become proficient in, and compliant with team requirements around the intake and documentation of various initiatives and progress within existing product management platforms (e.g., Jira).

Experience

• Education: MSc or PhD in Machine Learning, Data Science or similar discipline with robust statistical, data analysis, and machine learning competency (or equivalent experience)
• Hands-on experience working with directly with stakeholders in a business environment to provide data analytics support, create & present data visualizations, and devise ways to leverage various complex sources of data to generate actionable business insight.
• Mastery of common data science tools such as Python or R (and related code libraries), and experience using them to design and build predictive models for use in real-life business applications leveraging proprietary business datasets, to achieve defined performance improvement objectives.
• Preferred: a track record of deploying such models to end users; training users on how to interpret the outputs of the models and applying them to their regular business processes; and modifying/improving models over time to adapt to changing business needs.