For A Client Of Teamlease Digital
JOB DESCRIPTION: Deliver full pieces of a product analysis project that are integrated into overarching projects, with minimal assistance.
Analyze users, usage, trends, and relevant dimensions to provide insights on changing dynamics (e.g., demographics, devices, platforms, connection types).
Manage workload to maximize impact, prioritize multiple concurrent projects, and refine timelines with stakeholders as needed.
Plan and execute prioritized project work including selecting appropriate methods and advising on opportunities to improve data infrastructure.
Challenge
Identify and recommend creative ways to improve on solutions to defined problems via selection of better methods/tools.
Apply analytical techniques, core metrics, dashboarding infrastructure, and best data practices to novel problems.
Address commonly escalated issues or triage, when required, and clearly frame and escalate issues to be addressed by manager/stakeholders.
Influence
Work within one or more teams to communicate knowledge related to a broad set of tasks.
Identify key stakeholders to build a network by embedding within a working team to maximize context, communication, and contribute to cross-team collaboration.
Distill analysis into clear data visualizations while documenting underlying logic to allow other analysts or technical staff to study the analysis in greater depth.
Coordinate timelines, goals, and objectives for assigned component(s) of a project/process.
Contribute to shared team responsibilities and broader analyst community (e.g., by interviewing).Expertise
Demonstrate working knowledge of analytical techniques, and an understanding of related areas of the Google organization, including process impacts and upstream/downstream processes and functions.
Help develop a vision and roadmap for analytics across a product or functional group and communicate insights and results to stakeholders.
Responsibilities under the direction of Google Manager:
Analytical and statistical skills
Perform analyzes utilizing relevant tools (e.g., SQL, R, Python). Using comprehensive technical knowledge, use custom data infrastructure or existing data models, as appropriate. Formulate and interpret data to reach specific conclusions and next steps across projects. Design and evaluate statistical or heuristic models to examine defined problems with multiple potential solutions. Refine assumptions for model development.
Communication/influencing/stakeholder management
Provide analytical insights and recommendations to influence product feature development decisions, and with some guidance improve the overall, long-term product strategies in collaboration with the leadership team for a product/business area or the executives at a partner organization, with minimal assistance.
Data curation and validation, data infrastructure improvement
Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, and validate data to ensure quality. Review the dataset to ensure it is ready for analysis. Consider privacy, confidentiality, and security when extracting data. Define data quality and data processing requirements to solve defined problems with limited precedent for the data engineering teams to improve data infrastructure.
Problem framing/business acumen and intuition
Collaborate with stakeholders (e.g., product managers) across projects and teams to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or statistical models. Identify questions where data analysis will generate the most impact, with minimal assistance. Develop the roadmap and methodology to solve data-related questions based on preliminary information gathered on the product or domain. Define data requirements, data sources, formats, and analysis needed to creatively study the defined problem. Proactively address the likely concerns and challenges to the analyzes and models. Apply comprehensive knowledge in the field of specialization to identify the optimal methodology and tools based on available resources.
Product/Business review and inform product strategy and decision-making
Support in reporting Key Performance Indicators (KPIs) to support business reviews with the cross-functional and cross-organizational leadership team. Translate analysis results to business insights or product improvement opportunities.
Technical judgment (Product Analyst)
Build and prototype analysis and business cases iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed for product development.
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SKILLS/EXPERIENCE/EDUCATION:
Business acumen & intuition
Knowledge of structured problem-solving, communicating results, risk (e.g., considers business risks, leverages cross-functional teams).
Coding/Data extraction
Ability to extract relevant information from reading code in one or more core languages (e.g., Python, C++) and frameworksand ability to leverage the code as a resource to create work output for users or stakeholders.
Communication and active listening
Ability to clearly explain stats or domain knowledge to people not familiar with the subject matter or who lack a quant background. This includes the ability to explain reasons in a coherent, logical way that is very easy to understand by all. Leverage communication skills and active listening to manage stakeholders and to set proper technical direction for teams or orgs.
Data analysis and synthesis
Ability to analyze information, draw conclusions, generate alternatives and solutions, and evaluate outcomes. This includes the ability to use data to add value to business planning and strategies.
Data curation, validation, and cleaning
Ability to extract data and validate raw data to ensure it is valid and reliableand ability to clean data based on validation criteria and prepare for further analyzes.
Data intuition and data management
Ability to document analysis and modeling in statistical packages using open-source environments (e.g., Github, Python, R, ggplot, Altair). Ability to manage data in databases, including data transformation, data warehousing, and building data pipelines.
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For a Client of Teamlease Digital
3 to 5 Years
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