Senior Data Analyst

GroundTruth Analytics Role

GroundTruth is an advertising platform that turns real-world behavior into marketing that drives in-store visits and other real business results. We use observed real-world consumer behavior, including location and purchase data, to create targeted advertising campaigns across all screens, measure how consumers respond, and uncover unique insights to help optimize ongoing and future marketing efforts.

With this focus on media, measurement, and insights, we provide marketers with tools to deliver media campaigns that drive measurable impact, such as in-store visits, sales, and more.

Analytics team provides analytical support to multiple stakeholders (Product, Engineering, Business development, Ad operations) by developing scalable analytical solutions, identifying problems, coming up with KPIs and monitor those to measure impact/success of product improvements/changes and streamlining processes.

This will be an exciting and challenging role that will enable you to work with large data sets, expose you to cutting edge analytical techniques, work with latest AWS analytics infrastructure (Redshift, s3, Athena, and gain experience in the usage of location data to drive businesses. Working in a dynamic start up environment will give you significant opportunities for growth within the organisation.

A successful applicant will be passionate about technology and developing a deep understanding of human behaviour in the real world. They would also have excellent communication skills, be able to synthesise and present complex information and be a fast learner.

Location: Remote, India

You will:

• Define proper measurable metrics/variables for analyzing business problem and provide actionable recommendations
• Own a work stream completely, come up with interesting findings from data on your own
• Identify problems within an area and find solutions to it
• Frame out various hypotheses to solve root cause analysis problem
• Put tested hypothesis together to present a story/analysis to larger group/stakeholders
• Data Preparation: Exploratory Data Analysis (EDA) and feature engineering.
• Supervised vs. Unsupervised Learning: Understanding models that learn from labeled data (e.g., classification, regression) vs. discovering patterns in unlabeled data (e.g., clustering).
• Evaluation Metrics: Knowing how to test model accuracy, precision, and recall
• Has done one/many of these in previous/existing role: Root cause analysis, segmentation, clustering, linear regression, forecasting etc.
• Actively work/coordinate with data science/ data engineering to understand best practices used for coding/scripting and implement them within the team
• Actively discuss with different teams (Product, data science) to understand objective/business context of various projects

Minimum Qualifications:

Technical Skills (Must have)

• B.Tech degree (4 year) in Computer Science, Statistics, Mathematics, Economics or related fields
• 6 to 8 years of experience in working with data and conducting statistical and/or numerical analysis
• Ability to write SQL code (Advanced level)
• Strong hands-on experience on Python
• Using Jupyter Notebooks for EDA, root cause analysis
• Strong understanding of statistics
• Hands on experience in data visualisation tool like Looker/Tableau/Quicksight

Other Skills (Must have)

• Strong understanding of patterns/trends and draw insights from those
• Ability to tell a good story and support it with numbers and visuals
• Strong hold of handling instances that require root cause analysis/investigatory analysis
• Be willing and able to quickly learn about new businesses, database technologies and analysis techniques
• Go out of your way to help team members enhance technical skills
• Strong oral and written communication

Preferred Qualifications (Nice to have)

• Cross functional background with experience in software development/data engineering role
• Experience with AWS analytics infrastructure (Redshift, S3, Athena, Boto3)
• Exposure to AWS infra like lambda, step functions, Glue, EMR, exposure to Pyspark
• Experience working with large datasets
• Thorough understanding of machine learning concepts