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Job Responsibilities:

The following is a non-exhaustive list of responsibilities and areas of ownership:

• Collaborate with and serve as a 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.
• Understand and oversee data labeling/data annotation processes to ensure high-quality training datasets for machine learning models.
• Implement quality control measures and best practices in data annotation to ensure accuracy and consistency in machine learning projects.

Education:

• Master's or Ph.D. in Data Science, Computer Science, Statistics, or a related field.

Experience:

• 4+ 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.

Skills & Knowledge:

• 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.
• Familiarity with data labeling/data annotation processes and quality control measures to ensure accuracy and consistency in training datasets for machine learning models.

Additional Job Details: