The Business Analyst will provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, the candidate will serve as an analytics expert for our partners, using numbers to help them make better decisions.
The incumbent should weave stories with meaningful insight from data, make critical recommendations in Product Management. Should be a self-starter and relish tallying up the numbers one minute and communicating the findings to a team leader the next.
As a ground-floor member of the data services team, the candidate will gather, assess, and manage data, and transform it into beautiful insights, analysis and reporting. Should be a self-driven performer who takes a bit of chaos as a challenge, and thrives on creating structure and value out of complex and ambiguous technical challenges with little guidance. The candidate should be a team player with strong communications skills who’s eager to understand and work to the nuanced requirements of partners.
Roles & Responsibilities
Work with non-technical business users to understand their analytical needs. Document and prioritize requirements, to help them effectively use the data and analytical tools, developed by the team.
Design, develop and support data warehouses, dashboards, data pipelines and reporting tools for operational and business impact data. Design and enforce access control for all the data.
Work with business stakeholders and engineer teams to validate data, identify gaps and contribute to changes in business processes and data pipelines to fix data gaps.
Develop visualization based on user needs on dashboards or tableau.
Manage projects with end-to-end analytical drives, including project planning, finding the right teams and resources, requirement gathering, managing stakeholder expectations, working/collaborating with developers/engineers, developing data pipelines and reports, status update and readout to business stakeholders and management team.
Write and review technical documents, including requirements, schemas, design documents for existing and future data systems.
Experience with Unix or GNU/Linux systems including shell scripting.
Familiarity with one or more programming languages (Python, Java, C++, Ruby, etc.) Understanding of fundamental computing concepts including data structures and algorithms (including trees, graphs, file formats, algorithmic complexity).
Proficiency in a language for statistical computing (R, SAS, Stata).
Ability to prioritize multiple conflicting priorities while driving towards pragmatic decisions/actions.
Strong oral and written communication skills, including the ability to communicate complex findings in a structured and clear manner to a non-technical audience.
Education and Experience
Bachelor’s degree with an emphasis on quantitative or technical work (Computer Science, Statistics, Mathematics) or equivalent practical experience.
Experience working with and developing for non-technical users (defining requirements, explaining technical concepts to non-technical business users, etc.).
Experience in SQL and relational databases including queries, database definition and schema design.
Experience in designing data models and data warehouses, writing and maintaining ETLs which operate on structured and unstructured sources.
Experience in one or more visualization tools such as Tableau .
Experience in gathering reporting and analytics requirements from stakeholders.
Experience designing and executing structured analyses, deriving business insights, and evaluating the impact of business decisions; experience communicating findings to a diverse audience.
High level of comfort with a technology-driven, fast-paced environment that requires ability to quickly synthesize multiple sources of data.
Proven success record in managing multiple clients.
Knowledge and Competencies
Experience in working within global setting.
Strong organizational skills with the ability to work well under pressure and balance multiple projects.
Should be comfortable with data and love to wade into the complex details of data formatting, query messaging and bulletproofing pipelines.
Strong reporting and analytical skills.
Proven ability to create and monitor KPIs.
Ability to think “outside the box”.
Focused on results and extremely detail-oriented.