Offer summary

Qualifications:

1-2+ years in data analysis or related roles with hands-on experience in Python and SQL., Strong analytical thinking and problem-solving abilities., Proven skills in collecting, organizing, and analyzing significant amounts of information with attention to detail., Experience working in early-stage startups where you've built data processes from scratch..

Key responsibilities:

Own data collection strategies from start to finish, identifying necessary data and establishing quality protocols.

Conduct thorough research to inform product decisions, pricing strategies, and market positioning.

Use SQL and Python to analyze data and provide actionable insights for business decisions.

Create comprehensive research reports and presentations to communicate findings to the team.

Job description

Are you a hunter who thrives on extracting meaningful insights from data? Do you have a passion for scaling startups and want to be on the ground floor of something game-changing? Our client is a stealth-mode B2B SaaS startup, building a platform to transform how marketing teams and agencies collaborate. They are looking for a Data Analyst/Researcher to drive their data strategy and algorithm development through smart analysis and innovative thinking.

⚡ STARTUP REALISTS WANTED ⚡ This is a true 0-1 opportunity with pre-seed compensation but enormous upside potential. We're looking for someone who understands the early-stage journey and values equity + career growth over initial salary. As a 100% remote role, you'll enjoy location freedom while building something that could transform an industry. If you want to wear multiple hats, have outsized impact, and potentially see your contributions turn into significant rewards as we scale - this is your opportunity.

What You'll Do:

Own data collection strategies from start to finish - identifying what data we need, gathering information from various sources, and establishing data quality protocols.
Conduct thorough research to inform product decisions, pricing strategies, and market positioning.
Use SQL and Python to analyze data, discover patterns, and provide actionable insights that will guide business and product decisions.
Create comprehensive research reports and presentations to communicate findings to the team.
Work closely with developers to translate analytical findings into technical specifications for algorithm implementation.
Collaborate with the product team to ensure data collection and analysis align with business requirements.

Requirements

What You Bring:

1-2+ years in data analysis or related roles with hands-on experience in Python and SQL.
Strong analytical thinking and problem-solving abilities - you can break down complex challenges into solvable components.
Proven skills in collecting, organizing, and analyzing significant amounts of information with attention to detail and accuracy.
Experience with data modeling, database design development, and data mining techniques.
Strong understanding of statistical analysis and its practical applications.
Experience working in early-stage (0-1) startups where you've built data processes from scratch.
Excellent written and verbal communication skills – you know how to present insights clearly to technical and non-technical stakeholders.

Bonus Points:

Experience with ML/AI model creation and implementation.
Previous work in the martech, adtech, or agency world.
Knowledge of data visualization tools and techniques to present findings effectively.
Ability to collaborate with technical and business teams to align data strategy with broader company goals.
You bring creative approaches to data problem-solving.

Benefits

What We Offer:

A chance to make a real impact in a high-growth, early-stage startup.
100% remote work with a collaborative, global team - work from anywhere with flexible hours.
Direct access to founders and leadership team - your voice will be heard.
An opportunity to grow into a leadership role and help build our data team as we scale.
Freedom to experiment, learn, and shape our data infrastructure from the ground up.

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