Lead Data Scientist

Job Description We are seeking a Lead Data Scientist to drive advanced analytics and AI initiatives within our Product Quality Analytics organization. This role sits at the intersection of data science, product quality, and business strategy, and is responsible for leading high impact initiatives that transform complex data into scalable insights and intelligent systems. You will own the end-to-end lifecycle of data science solutions, from problem framing and modeling to deployment and adoption, while influencing stakeholders and mentoring team members. This is a highly visible role with the opportunity to shape how analytics and AI are embedded into quality decision making across the enterprise. Day to

Day:

• Leadership and Strategy ○ Lead the design and execution of advanced analytics and machine learning initiatives aligned to product quality and consumer insights ○ Partner with key stakeholders to define high value business problems and translate them into scalable data science solutions ○ Act as a thought leader in AI and machine learning, driving adoption of modern techniques including generative AI, natural language processing, and predictive modeling • Modeling and Analytics ○ Develop and deploy models such as classification, forecasting, anomaly detection, natural language processing, and causal inference ○ Apply statistical techniques such as regression, time series analysis, and experimentation to solve complex business challenges ○ Build frameworks for early signal detection, quality risk prediction, and root cause analysis • Productionization and Implementation ○ Collaborate with data engineering to productionize models using Google Cloud Platform tooling such as Agent Platform, Cloud Run, and Dataform ○ Contribute to scalable data products and pipelines that enable self service analytics ○ Ensure models are monitored, maintained, and continuously improved with an MLOps mindset • Collaboration and Cross Functional Partnership ○ Partner with data engineering, analytics, and business teams to align on priorities, data needs, and solution design ○ Work across teams to ensure data consistency, shared understanding of metrics, and scalable solutions ○ Bridge technical and non technical stakeholders by communicating clearly and driving adoption of data science solutions We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day.

We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.

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https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements

• Degree in Data Science, Statistics, Applied Mathematics, Computer Science, or a related field
• 5 or more years of experience in data science with demonstrated ownership of end to end projects
• Experience leading projects or mentoring team members in a formal or informal capacity
• Strong programming skills in Python or R
• Advanced SQL and experience working with large scale datasets
• Experience with machine learning frameworks
• Familiarity with cloud platforms, preferably Google Cloud (BigQuery, Vertex AI)
• Experience working with unstructured data such as documents, videos, or images is a strong plus
• Deep knowledge of statistical modeling techniques including regression, experimentation, and forecasting
• Experience with A B testing, causal inference, and predictive modeling
• Strong problem solving skills with the ability to connect data insights to business strategy
• Experience with prompt and context engineering
• Experience with agentic workflows and platforms
• Proven ability to influence stakeholders and drive decisions through data
• Strong communication skills with the ability to simplify complex topics
• Comfortable working in ambiguous and fast paced environments
• Demonstrated a growth mindset by staying curious and continuously learning, embracing challenges, and improving themselves.