Strategy & Value Consultant - Data Analyst

Company Description

We're not here to add to the noise. We're here to cut through it- with AI that actually works for marketers.

From AI-powered content creation to world-class CMS and the industry's most trusted experimentation platform, Optimizely is the tool modern marketers actually want to use. AI-Ready. Set. Go.

10,000+ brands including H&M, PayPal, and Zoom already get it. So do Gartner, Forrester, and IDC, who consistently recognize us as leaders in MarTech.

But here's the thing about building great products: it takes great people. Our 1,600+ Optimizers across 12 global offices are curious, collaborative, and refreshingly human. We don't do corporate speak. We do real conversations, big ideas, and genuinely care for the work we make together.

If you want to be part of a team that's shaping the future of marketing technology — and actually enjoys doing it — you're in the right place.

Find us on Instagram: @optimizely

Job Description

Introduction

We're looking for a Data Analyst to join the Strategy and Value Consulting (SVC) team at Optimizely. This role owns the data foundation behind our value consulting work: the source mapping, the models, the tables, and the analyses that our benchmarks, value models, and published research are all built on. 

Based in Dhaka, Bangladesh, you'll be the person who makes distributed, messy data usable. You'll map source systems, model them into analysis-ready tables, and run the complex analyses that turn raw product and customer data into numbers we can defend in front of an enterprise buyer. The three biggest parts of this job are mapping and modeling our data sources, building and maintaining the datasets the team runs on, and performing the deep analyses behind our benchmarks and research. 

This is a hands-on technical role, not a writing one. Our research and thought leadership are authored by a dedicated member of the team who depends on your work: you own the data and the analysis, and they own the narrative. What we need from you is rigor, reproducibility, and the ability to answer a hard question with data nobody has organized yet. 

Job Responsibilities

Data Mapping and Modeling: 

• Map and document our data landscape — product usage, customer, CRM, and third-party sources — including schemas, definitions, grain, coverage, and known quality issues 
• Design and build analysis-ready tables and data models the wider team can query without re-deriving logic every time 
• Establish and maintain consistent metric definitions so the same question returns the same answer across dashboards, value models, and published research 
• Own data quality: validation, reconciliation against source systems, and monitoring for breaks 

Data Engineering and Operationalization:

• Build and maintain repeatable pipelines to extract, transform, and load data from a variety of sources, including APIs, flat files, and third-party datasets 
• Turn one-off analyses into maintained datasets with automated refreshes 
• Optimize queries and models for performance against large tables 
• Document transformation logic end to end so any published number can be traced back to source 

Analysis: 

• Perform complex analyses on large datasets: segmentation, cohort and time-series analysis, significance testing, correlation, and regression 
• Produce the quantitative foundation for industry benchmarks, maturity models, and industry-specific value models 
• Supply the datasets, analyses, and methodology notes behind our white papers and research reports, partnering with the team member who writes them 

Dashboards and Reporting: 

• Create and maintain dashboards for internal use, focused on customer benchmarks, performance metrics, and presales reporting 
• Build reporting stakeholders can self-serve, rather than re-requesting the same cut of data 
• Be the team's go-to resource for all data needs 

Collaboration and Communication: 

• Work with internal stakeholders to identify key data requirements and make sure data is accurate and consistent 
• Partner with cross-functional teams (Marketing, Product, Engineering, and Revenue Operations) to get access to the data we need and to understand how it's generated 
• Explain methodology, assumptions, and caveats clearly to non-technical stakeholders 
• Support live enterprise pursuits with the analysis behind tailored, insight-driven customer briefs 

What Makes This Role Unique:

• Embedded within a revenue-facing consulting function 
• Direct exposure to enterprise value discussions 
• End-to-end ownership of the data foundation, from raw source to published insight 
• Opportunity to build the analytical infrastructure for value selling from the ground up 

Qualifications

Knowledge and Experience

Required:

• 3+ years of hands-on experience as a Data Analyst, Analytics Engineer, or Data Engineer 

• Advanced SQL — window functions, CTEs, complex joins, and query optimization against large tables 

• Demonstrated experience modeling raw data into analysis-ready tables, not only querying tables someone else built 

• Experience integrating data from multiple disparate sources, including APIs and semi-structured formats such as JSON 

• Proficiency in Python (or R) for data manipulation and statistical analysis 

• Hands-on experience with a cloud data warehouse such as Snowflake, BigQuery, or Redshift 

• Strong working knowledge of Power BI (or Tableau or Looker) for dashboard development 

• Solid grounding in statistics: significance testing, confidence intervals, and the judgment to know  

• Clear written communication — enough to document methodology and explain caveats to non-technical colleagues 

• Strong analytical and problem-solving skills with a keen eye for detail 

• Solid organizational skills and the ability to manage multiple projects at once 

Preferred:

• Experience with transformation or orchestration tooling (dbt, Airflow, or similar) 

• Experience with go-to-market and product data models (Salesforce, product telemetry, billing data) 

• Familiarity with ROI or value-based modeling frameworks 

• Hands-on experience with AI tools applied to data work (for example, query generation, code assistance, or data profiling) 

• Exposure to SaaS, MarTech, or consulting environments 

Education

• Bachelor of Science, Bachelor of Arts, or equivalent work experience required 

• Background in Computer Science, Data Science, Statistics, Engineering, Economics, or Business Analytics preferred 

Additional Information

At Optimizely, our standardized language is English, and it is crucial to have good English communication skills to be successful in your global role. All our external and cross-location communication is done in US English (en-us), but internally you can speak in whichever native language you most identify with.

Optimizely is committed to a diverse and inclusive workplace. Optimizely is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.