Go-To-Market Data Analyst
з/п не указана
Создаём бесконечную онлайн-доску для работы кросс-функциональных команд.
Продуктом пользуются лучшие компании и стартапы мира: Netflix, Ikea, Cisco, Twitter, Autodesk, Logitech, Upwork, Instapage, SAP.
Miro is the leading visual collaboration platform helping cross-functional teams ideate, design think and collaborate to bring some of the world’s most innovative products on the planet to market, faster. Over 3 M managers, designers, agile coaches, marketers, and other professionals are involved in the process of new products and services development in Miro. We have 10K+ paying accounts from world's most successful and innovative companies, including teams inside Netflix, Twitter, Skyscanner, Qlik, Upwork, Expedia, Spotify, eBay, Cisco, Sapient, Geometry, Unbounce, Autodesk, PwC, Deloitte and others.
Go-to-market (GTM) strategy is integrated actions of Marketing, Sales, Growth, Customer Success, Product teams aimed to deliver valuable product for right customers to enable rapid growth of Miro's active user base and revenue. GTM-related data analytics is focused on all stages of customer lifecycle (acquisition, onboarding, conversion to paid, expansion, retaining, reactivation) for both Enterprise and Self Serve segments aiming to bridge the data and decision makers. We consider Data Analyst is a bi-direction driver. On the one hand, he transforms business goals to data requests and reports/dashboards, on the other he proactively explores data to bring insights and drive right resolutions.
- Rolling-out ‘data-as-a-service’ approach for Marketing/Sales/Success/Support functions to make data easy to access, understand and make decisions.
- Communicate with Marketing/Sales/Success/Support and cross-functional teams, defining metrics they track, planning report structures, making it visually appealing and easy to understand, and automating the reporting process our BI system (we use Looker).
- Explore users’/teams’/logos’ behavior to extract valuable insights to support CRM strategies.
- Provide data-driven segmentation to support ‘out-of-product’ customer engagement initiatives (marketing campaigns, sales development and expansion campaigns, etc).
- Measure the impact of GTM initiatives and render analytical support for A/B tests.
- Do ad hoc research: if something emerges in the data like a significant increase in churn or drop down in sign-ups from specific acquisition channel, you have to find out “why?”. Reports and researches should not come just in the form of numbers and distributions, but rather in the form of action items (e.g., to increase X, we have to do Y).
- Develop data documentation (glossary, data models, etc.) to cover dedicated domains within the company.
- In collaboration with data scientists elaborate ML models for attribution, scoring, segmentation, churn prediction, etc.
- In collaboration with data engineers optimize data workflows, control for data consistency and coverage across dedicated domains and IT solutions (Looker, Hubspot, Salesforce, etc.).
Required skills & experience
- Warranted analytical skills.
- 1+ years of data analytics work experience.
- Intermediate in statistical methods, experimental design, using quantitative analysis to impact key decisions.
- Experience writing SQL queries and working with large data sets.
- Understanding database structures and metadata standards.
- Experience in product analytics and BI tools (eg. GA, Kissmetrics, Amplitude, Looker, Tableau, or similar).
- Experience in delivering analytical solutions for complex GTM tasks (acquisition, retention, pricing, up/cross-selling, etc.).
- Understand overall business value, rather than think and care just about numbers and charts.
- The ability to influence stakeholders and work closely with them to determine acceptable solutions.
- High-level written and verbal communication skills.
- English language skills at upper intermediate level (or higher).
Nice to have
- Programming skills in R/Python.
- Experience in collaboration with data engineers on elaborating data model and supporting its consistency.
- General knowledge of data science methods and applications.
Stack, infrastructure, tools
- Data Infrastructure: Spark, Hadoop, Hive, Kafka, PostgreSQL, Presto, Looker.
- Standard python/R data science tools.
- Git, Jira, Confluence, Miro.
Perks & Benefits
- Work in an international team, a possibility to become a valuable player in the ambitious, highly motivated and efficient team.
- Highly competitive salary.
- Stock option grant in accordance with company policy.
- Great professional and financial growth perspectives.
- Compensation for any professional courses.
- Any professional literature ordered by request.
- Sports activities and corporate tournaments.
- Regular educational and informal corporate events.
Kitchen in the office with everything you need for a snack, breakfasts and dinners at the office.
Health insurance for you and your family.
- A comfortable workplace equipped by your request.
- A modern office in a loft in the city center with free parking, a river view, a volleyball court, and a restaurant.
- Help with relocation.
- Office location: Perm, Reshetnikovskiy spusk, Digital Port.
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