Lead Data Scientist (Analytics) - Fulfilment

Company Description

Life at Grab

At Grab, every Grabber is guided by The Grab Way, which spells out our mission, how we believe we can achieve it, and our operating principles - the 4Hs: Heart, Hunger, Honour and Humility. These principles guide and help us make decisions as we work to create economic empowerment for the people of Southeast Asia.

Job Description

Get to know the team

The Fulfilment Tech Family is at the heart of enabling Grab to outserve our consumers and partners in different businesses and marketplaces across Southeast Asia. Our mission is to offer the best-in-class products and experiences to our driver partners as to increase adoption and engagement of our services. Improve driver partner opportunities and efficiency in order to fulfill consumer orders without fail, rain or shine. And to create efficient marketplaces by determining an optimal price that is both sustainable and loved by our partners and consumers.


The Fulfilment Product Analytics Team advances product innovation with analytics and experimentation best practices. We ship a large number of features and that means tuning models, evaluating changes and running experiments to drive better outcomes for our driver partners and millions of customers across South East Asia.

Your role is to guide a data-first approach to product thinking, design controlled experiments and be objective while evaluating results, all of this while working with stakeholders to evaluate new and innovative product and business ideas! You will help developers, designers & product managers across the company with recommendations on how to learn from unexpected results, study underlying causes for them and iterate on the next set of products to build for our users.

Get to know the job

You will be working closely with various teams within a business line (Product, Business, Engineering, Design and Data Science) to understand data requirements, identify and track key metrics, and provide data-driven insights. You will also work with stakeholders to evaluate the feasibility of new business/product ideas and provide appropriate recommendations.

The Day-to-Day Activities

• Understand business objectives and deepdive into existing data to recommend new product ideas to solve for the most impactful customer problems

• Use data to identify trends, spot anomalies and delve deeper into their root causes

• Use your number-crunching and slide-maker skills to use and present data beyond just numbers. Hone your data storytelling skills through visualisation techniques by building dashboards and presenting insights to a non-technical audience!

• Discuss and align with stakeholders on key product metrics, design and propose experimentation strategies

• Launch A/B tests, analyze experiment results and provide recommendations

• Design and own frontend and backend data specs for new products, while collaborating with engineering teams to ensure accurate and timely data collection

• Develop and maintain data pipelines to fulfill product reporting requirements

• Mentor junior team members, supporting their professional development in both hard and soft skills

• Identify frequently occurring hypotheses and problem statements that can be generalised into common patterns. Develop scalable analytical frameworks and solutions to allow for solving repetitive problems in a more efficient manner

• Role-model high standards of rigour in how we do measurements, experimentation, analyses and recommendations. Safeguard the integrity of how data is used and understood to ensure we maintain objectivity in our reasoning, actions and decision making

• Evaluate the feasibility of developing new products, participate in user researches to validate customer problems

Qualifications

The Must-Haves

• 6+ years of experience working in data-related and/or quantitative fields, including but not limited to Analytics and Applied Data Science

• Fluent with SQL, Python, R or other scripting/programming languages to problem-solve. Experienced with working with very large datasets

• Strong data visualization and storytelling skills. Experience in creating dashboards using PowerBI / Superset / Tableau or other visualisation tools

• Exposure to data pipeline creation and data engineering tools such as Chimera, Airflow, Presto, Databricks etc

• Effective communication and collaboration skills and the ability to present complex subjects coherently to diverse audiences comprising generalists and specialists

• Self-motivator and an ability to learn independently

• Ability to deliver on tight timelines and move quickly with cross-functional teams to partner or lead decision making while maintaining high attention to detail

• A culture role model of our 4Hs: Honour, Humility, Hunger and Heart

The Nice-to-Haves

• Relevant industry experience (preferably in an Internet or ‘Direct to Consumer’ company with high velocity data and scaled controlled experiments) and/or prior experience with Product Management or business-facing operations will be a plus

• Experience with designing, conducting and analysing controlled A/B experiments

• Prior experience with supervised (eg : predictive modeling - regressions/classifications) and unsupervised (eg : clustering, segmentation) ML algorithms

Additional Information

Our Commitment

We recognize that with these individual attributes come different workplace challenges, and we will work with Grabbers to address them in our journey towards creating inclusion at Grab for all Grabbers.