Applied Scientist II

Full Job Description

Discover and apply insights from massive data sets of structured, semi-structured, and unstructured data. Identify opportunities to leverage available data to resolve customer pain points. Own data science projects end to end starting from problem definition, data exploration/preparation, model building, and model evaluation. Develop and deploy machine learning, deep learning, and LLM-based solutions for conversion understanding, user profiling, identity linking, and commerce intelligence scenarios. Prototype and rapidly evaluate creative ideas to gain insights into their strengths and weaknesses. Partner with engineering and product teams to translate scientific innovations into scalable production systems. Storytelling and visualization capabilities to deliver the right message to the concerned audience. Design metrics that serve as the North Stars for team efforts and A/B testing framework to support data-driven decisions. Drive experimentation and data-driven decision making through rigorous offline and online evaluation methodologies. Stay current with emerging trends in AI, machine learning, NLP, recommender systems, and user behavior modeling. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience. 5+ years of industry experience as an Applied Scientist. Hands-on experience in large language models (LLMs), pretrained language models (PLMs), machine learning (ML), and deep learning (DL). Data-centric and analytical mindset with a solid focus on experimentation and measurable impact. Problem-solving skills and good understanding of algorithms and data structures. Fluency with at least one programming language such as Python, C#, Java, or Scala. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. Ability to learn quickly, work independently in complex situations, and deal with ambiguity. Experience with big data platforms and distributed processing technologies. Hands-on experience in NLP, information retrieval, ranking, or recommendation systems. Understanding of data analytics and visualization tools. Experience working with customer behavior data, user journeys, digital analytics, or advertising systems. Communication and collaboration skills with the ability to influence cross-functional stakeholders.

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