Lead Data Scientist (Analytics) - Digital Marketing
Jakarta, Indonesia
- Pay
- Pay not listed
- Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingYou'll work on end-to-end paid marketing analytics initiatives.
From the employer’s posting
Get to Know the Role We are seeking Data Scientist with deep expertise in paid marketing measurement, AI-driven analytics, and operations to join our growing team. In this role, you'll collaborate with marketing leaders, analytics teams, and cross-functional stakeholders to solve complex digital marketing challenges using advanced measurement science, artificial intelligence, and data-driven approaches. You'll work on end-to-end paid marketing analytics initiatives. You will directly report to the Senior Manager. You will be based onsite.
What you’ll bring
All qualificationsCore experience
- 6+ years in data science and analytics, including 3+ years in paid marketing measurement and operations.
- Expertise in attribution modeling, including multi-touch, algorithmic, and rule-based approaches.
- Experience designing incrementality studies, A/B tests, holdout analyses, and geo-lift studies.
- Hands-on experience building, optimizing, and deploying machine learning models for marketing.
- Proficiency in Python, SQL, Pandas, Scikit-learn, and Spark; familiarity with causal inference tools such as CausalML, DoWhy, or EconML.
- Experience with cloud data platforms, marketing datasets, ad platform APIs, and ETL pipelines.
Qualification wording
6+ years in data science and analytics, including 3+ years in paid marketing measurement and operations.
Expertise in attribution modeling, including multi-touch, algorithmic, and rule-based approaches.
Experience designing incrementality studies, A/B tests, holdout analyses, and geo-lift studies.
Hands-on experience building, optimizing, and deploying machine learning models for marketing.
Proficiency in Python, SQL, Pandas, Scikit-learn, and Spark; familiarity with causal inference tools such as CausalML, DoWhy, or EconML.
Experience with cloud data platforms, marketing datasets, ad platform APIs, and ETL pipelines.
Tools in this posting
- Python
- SQL
- Spark
- pandas
- scikit-learn
Source — Tool mentions in context
- Hands-on experience building, optimizing, and deploying machine learning models for marketing. - Proficiency in Python, SQL, Pandas, Scikit-learn, and Spark; familiarity with causal inference tools such as CausalML, DoWhy, or EconML. - Experience with cloud data platforms, marketing datasets, ad platform APIs, and ETL pipelines.
- Develop AI and machine learning solutions to improve campaign targeting, bidding, experimentation, and measurement workflows. - Build scalable data pipelines integrating paid media, conversion, and internal data using SQL, Spark, and cloud technologies. - Create analytics tools and dashboards to track campaign performance, acquisition costs, and marketing ROI.
About Grab
Grab is Southeast Asia's leading superapp.
In the employer’s words · Read in context
Posting record
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- Live
- First seen by us
- Oct 23, 2026 · 8 days ago
- Recorded sightings
- 59
- Last seen by us
- Oct 31, 2026
- Reposted
- once since Sep 4, 2026
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Job description
Job Description
Get to Know the Team
The Growth Data Science team is a key component of our regional growth strategy. We focus on creating and implementing innovative approaches to drive growth through performance marketing automation, machine learning models, geospatial insights, user lifecycle and funnel optimisation, behavioural forecasting, and other advanced analytics methods. Our work spans across transportation, food, fintech, logistics, and platform services.
Get to Know the Role
We are seeking Data Scientist with deep expertise in paid marketing measurement, AI-driven analytics, and operations to join our growing team. In this role, you'll collaborate with marketing leaders, analytics teams, and cross-functional stakeholders to solve complex digital marketing challenges using advanced measurement science, artificial intelligence, and data-driven approaches. You'll work on end-to-end paid marketing analytics initiatives.
You will directly report to the Senior Manager. You will be based onsite.
The Critical Tasks You Will Perform
- Partner with marketing stakeholders to align measurement strategies with business goals, channels, and data constraints.
- Select and apply attribution, incrementality, and causal inference methods, explaining trade-offs and recommendations.
- Design and run experiments—including A/B tests, holdouts, matched markets, and geo-lift studies—to measure campaign impact.
- Build and maintain Media Mix Models (MMM) to assess channel effectiveness, guide budget allocation, and forecast performance.
- Develop AI and machine learning solutions to improve campaign targeting, bidding, experimentation, and measurement workflows.
- Build scalable data pipelines integrating paid media, conversion, and internal data using SQL, Spark, and cloud technologies.
- Create analytics tools and dashboards to track campaign performance, acquisition costs, and marketing ROI.
- Conduct exploratory analysis and statistical modeling; validate models and translate findings into actionable recommendations.
- Manage project plans, document methodologies, and communicate insights clearly to technical and non-technical stakeholders.
- Collaborate across marketing, analytics, product, and engineering teams; mentor junior analysts and data scientists.
Qualifications
What Essential Skills You Will Need
- 6+ years in data science and analytics, including 3+ years in paid marketing measurement and operations.
- Expertise in attribution modeling, including multi-touch, algorithmic, and rule-based approaches.
- Experience designing incrementality studies, A/B tests, holdout analyses, and geo-lift studies.
- Strong background in Media Mix Modeling (MMM) or marketing mix optimization.
- Hands-on experience building, optimizing, and deploying machine learning models for marketing.
- Proficiency in Python, SQL, Pandas, Scikit-learn, and Spark; familiarity with causal inference tools such as CausalML, DoWhy, or EconML.
- Experience with cloud data platforms, marketing datasets, ad platform APIs, and ETL pipelines.
- Familiarity with generative AI and LLMs for automating insights and reporting.
Additional Information
Life at Grab
We care about your well-being at Grab, here are some of the global benefits we offer:
- We have your back with Term Life Insurance and comprehensive Medical Insurance.
- With GrabFlex, create a benefits package that suits your needs and aspirations.
- Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
- We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.
- Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours
What We Stand For At Grab
We are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.
Company Description
About Grab and Our Workplace
Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.
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- Pay
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- Location & working pattern
Jakarta, Indonesia
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