Business & Marketing Data Scientist (III) at Mindlance in Mountain View, CA

Job description

• Description

Responsibilities

• As a Business & Marketing Data Scientist, you are a subject matter specialist for translating business problems from your supported organization or functional area into analytical solutions and insights. You provide technical mentorship in delivering project work including implementing data science solutions, improving data pipelines, developing evaluation metrics, or building statistical models that provide insights to the business. You create and implement reused and scaled solutions within the team's development process. You collaborate with supported teams and win stakeholder trust by translating business needs into tractable analyses or evaluation metrics. You work closely with product and engineering teams to analyze impact on product or our metrics (including daily activities, retention, churn). Responsibilities include:
• - Formulate and interpret data to reach specific conclusions and next steps as a key project contributor.
• - Scale existing or create repeatable solutions (e.g., best practices recommendations, tutorials, blog articles, sample code) and ensure effective documentation of repeatable solutions.
• - Write and review solution code, produced to our standard and integrated with other production code, in collaboration with internal or external developers, users, customers, or partners (as needed).
• - Help develop the roadmap and methodology to solve data-related questions based on preliminary information gathered on the product or domain. Help define data requirements, data sources, formats, and analysis needed, anticipate and proactively address the likely concerns and challenges to the analysis and models. Help identify optimal methodology and tools based on available resources.
• - Drive implementation and execution of recommended changes in collaboration with other teams. Drive ongoing analysis to drive product excellence or system optimization as needed.
• - Help drive gathering, extraction and compilation of data across sources via relevant tools (e.g., SQL, R, Python). drive formatting, re-structuring, and validation of data to ensure quality. drive review of datasets to ensure they are ready for analysis. Consider privacy, confidentiality, and security when extracting data.
• - Help other teams leverage data to prioritize work tasks and impact by driving identification of Objectives and Key Results (OKRs). Use data to help make business decisions, answer statistical-based questions, and refine parameters and methods. Drive feedback on other teams' work from a quantitative perspective by checking and validating assumptions.
• - Collaborate with stakeholders to identify and clarify business or product questions to answer. Provide feedback to translate and refine complex business questions into tractable analysis, evaluation metrics, or statistical models. Identify questions where data analysis will generate the most impact.
• - Assess and identify gaps and issues in current products based on user feedback or metrics analysis. Communicate product gaps and issues to internal teams (e.g., Product Management, Business Development, Engineering). Contribute to solving gaps and issues by technical contribution that can take the form of developing, validating, and documenting new features/solutions.
• - Drive review of analysis and business cases conducted by others to provide feedback. Address analytical challenges as a technical expert.
• - Develop and define metrics to track and evaluate solution implementation and deployment. Create dashboards or tools to automate work processes, generate reports to internal teams and external customers/partners, or inform product/solution decisions.

Requirements

• - Identify and interface with relevant stakeholders to learn about the domain. Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.Minimum role qualification requires proficiency in:
• - Statistics/domain expertise and problem framing
• - Data intuition and management
• - Programming (Business Data Scientist)
• - Communication and active listening
• - Data science leadership

Skills

Required

• Data intuition and management
• Programming (Business Data Scientist)
• Communication and active listening
• Data science leadership

Benefits

• Health insurance
• 401(k)
• Dental Insurance
• Vision Insurance
• Referral Program
• Travel Allowances