Analyst at Vida Shoes International
India
INR 70k - INR 100k
<p class="MsoNormal"><strong>The Role</strong></p><p class="MsoNormal">As our Analyst, you'll be the analytical engine behind our online sales and paid acquisition. You'll track how every channel performs, find where we're winning or wasting spend, and give marketing, merchandising, and leadership clear recommendations. The role suits someone equally comfortable in a spreadsheet, a SQL editor, and a conversation with a media buyer.</p><p class="MsoNormal"><strong>Compensation</strong>: Indian Rupee $70,000 - $100,000 montly&nbsp;</p><p class="MsoNormal"><strong>What You'll Do</strong></p><ul style="margin-top: 0in;" type="disc"><li class="MsoNormal" style="mso-list: l2 level1 lfo1; tab-stops: list .5in;">Own reporting on ecommerce performance (traffic, conversion rate, AOV, revenue, margin) and paid media (ROAS, CAC, CPA, CTR, CPM) across Google, Meta, TikTok, Amazon Ads, affiliates, and other channels.</li><li class="MsoNormal" style="mso-list: l2 level1 lfo1; tab-stops: list .5in;">Build and maintain dashboards in [Looker Studio / Tableau / Power BI] that give teams a single source of truth.</li><li class="MsoNormal" style="mso-list: l2 level1 lfo1; tab-stops: list .5in;">Analyze campaign and channel performance, and recommend budget allocation and bid, audience, and creative optimizations.</li><li class="MsoNormal" style="mso-list: l2 level1 lfo1; tab-stops: list .5in;">Design, run, and read A/B tests on landing pages, site experience, promotions, and ad creative.</li><li class="MsoNormal" style="mso-list: l2 level1 lfo1; tab-stops: list .5in;">Evaluate attribution across channels using platform data, GA4, and incrementality or MMM approaches where available.</li><li class="MsoNormal" style="mso-list: l2 level1 lfo1; tab-stops: list .5in;">Analyze customer behavior, including cohorts, retention, lifetime value (LTV), repeat purchase rates, and LTV:CAC by channel.</li><li class="MsoNormal" style="mso-list: l2 level1 lfo1; tab-stops: list .5in;">Support merchandising and promotional planning with product, category, pricing, and discount performance analysis.</li><li class="MsoNormal" style="mso-list: l2 level1 lfo1; tab-stops: list .5in;">Forecast revenue and marketing spend for weekly, monthly, and seasonal peaks such as Black Friday/Cyber Monday and holidays.</li><li class="MsoNormal" style="mso-list: l2 level1 lfo1; tab-stops: list .5in;">Audit tracking and data quality (pixels, UTMs, conversion APIs, GA4 events) with marketing and engineering.</li><li class="MsoNormal" style="mso-list: l2 level1 lfo1; tab-stops: list .5in;">Present findings to non-technical stakeholders with clear, actionable recommendations.</li></ul><p class="MsoNormal"><strong>What You Bring</strong></p><ul style="margin-top: 0in;" type="disc"><li class="MsoNormal" style="mso-list: l0 level1 lfo2; tab-stops: list .5in;">2&ndash;4 years of experience in ecommerce, digital marketing, or retail analytics.</li><li class="MsoNormal" style="mso-list: l0 level1 lfo2; tab-stops: list .5in;">Strong SQL skills and advanced Excel/Google Sheets.</li><li class="MsoNormal" style="mso-list: l0 level1 lfo2; tab-stops: list .5in;">Hands-on experience with GA4 and at least two major ad platforms (Google Ads, Meta Ads Manager, TikTok Ads, Amazon Advertising).</li><li class="MsoNormal" style="mso-list: l0 level1 lfo2; tab-stops: list .5in;">Experience building dashboards in a BI tool.</li><li class="MsoNormal" style="mso-list: l0 level1 lfo2; tab-stops: list .5in;">Solid grasp of performance marketing metrics, funnel analysis, and attribution concepts.</li><li class="MsoNormal" style="mso-list: l0 level1 lfo2; tab-stops: list .5in;">Working knowledge of A/B testing and basic statistics (significance, sample size).</li><li class="MsoNormal" style="mso-list: l0 level1 lfo2; tab-stops: list .5in;">The ability to explain complex data simply and turn analysis into a clear "here's what we should do."</li><li class="MsoNormal" style="mso-list: l0 level1 lfo2; tab-stops: list .5in;">Attention to detail and a healthy skepticism about data quality.</li></ul><p class="MsoNormal"><strong>Nice to Have</strong></p><ul style="margin-top: 0in;" type="disc"><li class="MsoNormal" style="mso-list: l1 level1 lfo3; tab-stops: list .5in;">Python or R for analysis or automation.</li><li class="MsoNormal" style="mso-list: l1 level1 lfo3; tab-stops: list .5in;">Experience with Shopify, Magento/Adobe Commerce, or Salesforce Commerce Cloud.</li><li class="MsoNormal" style="mso-list: l1 level1 lfo3; tab-stops: list .5in;">Familiarity with marketing mix modeling, incrementality testing, or tools like Northbeam, Triple Whale, or Rockerbox.</li><li class="MsoNormal" style="mso-list: l1 level1 lfo3; tab-stops: list .5in;">Experience with CRM and email/SMS platforms (Klaviyo, Braze, Attentive).</li><li class="MsoNormal" style="mso-list: l1 level1 lfo3; tab-stops: list .5in;">Experience with data warehouses (BigQuery, Snowflake) and dbt.</li></ul><p class="MsoNormal">#LI-REMOTE</p>
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