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.
MAIN PURPOSE OF JOB
We are seeking a highly skilled and motivated Data Scientist to join our Data Operations and Analytics team. This individual will play a critical role in achieving our team's vision of fully harnessing the wealth of data available to us, and measurably driving business performance across the entire Welocalize organization. This role will utilize advanced data science and deep analysis techniques to derive actionable insights, build advanced predictive models, and collaborate cross-functionally to drive data-driven decisions. The ideal candidate will engage productively with Analysts, business stakeholders, and data engineers to understand business goals and develop insights that lead to tangible business value.
MAIN DUTIES
The following is a non-exhaustive list of responsibilities and areas of ownership:
Collaborate with and serve as resource to Analytics Specialists to elevate our data analyses, introducing advanced modeling techniques and achieving deeper insights.
Develop an understanding of the business, its priorities, and how the wealth of available data connects to those priorities—then proactively identify opportunities to leverage advanced analytical techniques to drive improved outcomes.
Design and implement predictive models to forecast business metrics, such as revenue, demand, capacity & outputs, on-time delivery, customer churn, and so forth.
Devise, propose and conduct A/B testing and other experimental designs to validate business hypotheses and strategies.
Engage in text analytics, anomaly detection, and deep learning projects as relevant to business needs.
Work closely with the Data Operations Engineering team to ensure data availability, quality, and accessibility. Potentially contribute to data operations engineering activities, e.g. ETL configurations and builds for complex, high-value datasets relevant to analytical activities and/or business priorities.
Visualize complex data insights in a comprehensible manner for non-technical stakeholders.
Stay up-to-date with the latest techniques in data science and introduce innovative solutions to relevant business problems.
REQUIREMENTS
Education Level
Master's or Ph.D. in Data Science, Computer Science, Statistics, or a related field.
Experience
3+ years proven experience in predictive modeling, machine learning, and statistical analysis in an applied business context leading to measurable business outcomes.
Experience with NLP and its applications in a business context preferred.
Relevant Skills
Expert proficiency in SQL as well as programming languages such as Python and/or R.
Ability to connect technical analytical activities to business objectives with a value outcome-oriented mindset; comfortable being evaluated on the basis of measurable impact.
Robust familiarity with data visualization tools, especially Microsoft PowerBI.
Strong English-language communication skills; able to engage, collaborate with, and influence stakeholders at all organizational levels, potentially including external clients.
Strong problem-solving skills and the ability to communicate complex data insights in a clear and concise manner.
Adaptability and willingness to contribute to a diverse range of initiatives; comfort managing multiple ongoing projects and priorities.
Ability to contribute in varying capacities as part of cross-functional teams spanning the entire organization.
