892 Data Science jobs in Indonesia

Pengalaman kerja minimal 2 tahun Pendidikan minimal S1, diutamakan Teknik Komputer, Informatika, Sistem Informasi, Ilmu Komputer. Menguasai Bahasa pemrograman seperti Phyton atau R

Who are we?

Artefact is a new generation of a data service provider, specialised in data consulting and data-driven digital marketing.

Our purpose?

Every day we boost our clients' data transformation into business impact across the entire value chain of organisations.

Our strength?

Our data services stand on a double expertise: the combination of Artificial Intelligence and the business prowess acquired from our customers around the world, such as AccorHotels, Orange, Carrefour, Engie, Samsung, L'Oréal, Nissan.

Artefact's success comes from a unique mix of company assets: cutting-edge data technologies, agile methodologies for fast delivery, cohesive teams assembling the finest business consultants, data analysts, data scientists, data engineers, and digital marketing experts.

Artefact is :

• 23 offices in Paris, London, Shanghai, Dubai.
• 1700 employees
• 4 practices: Data Consulting, Data Marketing, Activation and Creation

What you will be doing:

Key responsibilities

As a Data Director, your role will encompass:

Strategic Leadership and Management

• Lead and expand the data science team, ensuring alignment with the company's strategic objectives.
• Develop and oversee the execution of ambitious data transformation projects, ensuring they meet client needs and business goals.
• Drive collaboration across different divisions—such as Activation, Creativity, and Strategy—to deliver comprehensive, integrated solutions that enhance client satisfaction and service delivery.

Client Engagement and Relationship Management

• Build and maintain senior-level relationships with clients, becoming a trusted advisor for their data strategy and transformation efforts.
• Regularly present insights and strategic recommendations to clients and internal stakeholders, showcasing the value and impact of data-driven decision-making.

Operational Excellence and Innovation

• Ensure the successful delivery of data projects, setting high standards for timeliness and quality.
• Spearhead the adoption of cutting-edge data science and data engineering technologies, methodologies, and practices.
• Promote a culture of continuous improvement and learning within the data science team, encouraging innovation and experimentation.

Team Development and Thought Leadership

• Mentor and develop team members, fostering a collaborative and empowering environment.
• Act as a thought leader in data science, contributing to the broader data science community and enhancing Artefact's reputation in the industry.
• Ensure the team's technical capabilities align with industry standards and emerging technologies, facilitating ongoing professional development and training.

Qualifications: Education & experience required

• A Master's or PhD degree in Machine Learning, Mathematics, Computer Science, or a related field.
• Over 8 years of experience in leadership roles within data science, demonstrating a proven track record of managing teams and delivering impactful data-driven solutions.
• Exceptional knowledge of data processing, data modeling, algorithms, and data architecture, with hands-on experience in managing large-scale projects.
• Strong leadership skills, with the ability to inspire, motivate, and guide team members towards achieving business and personal growth goals.
• Excellent communication and interpersonal skills, capable of engaging effectively with all levels of the organization and external clients.

In addition, you have the knowledge in one or more of the following technologies:

• Google Cloud Platform resources (Big Query, Google Cloud Storage) or its equivalent in Azure or AWS
• You know how to connect to an API through the knowledge of the different authentication method (OAuth, HTTP Basic, API key)
• Advertising tool, linked to tracking and/or analytics in a marketing context (Google Analytics, Adobe Analytics, DMP, DSP, Adservers, DV
• ETL tool (Airflow, Dataiku, Dataflow, Dataprep.)
• Web application (R-Shiny, Python Flask) that you have industrialized

What we are looking for

• A Doer:
  you get things done and inspire your team to do the same
• An Analyst:
  you LOVE data and think every company should take their decisions based on facts
• A Pragmatist:
  you have a no-nonsense mindset that seeks for practical and realistic solutions
• A Mentor:
  your clients and colleagues naturally seek you out for advice
• An Adventurer:
  you're an entrepreneur constantly looking for business opportunities

Why you should join us

• Artefact is the place to be:
  come and build the future of marketing
• Progress:
  every day offers new challenges and new opportunities to learn
• Culture:
  join the best team you could ever imagine
• Entrepreneurship:
  you will be joining a team of driven entrepreneurs. We won't give up until we make a huge dent in this industry

Come join us

About The Role:

To apply data science techniques and machine learning algorithms to solve business problems, improve decision-making, and ensure the efficient deployment of models in production.

What Will You Do:

• Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
• Analyzing the ML algorithms that could be used to solve a given problem
• Exploring and visualizing data to gain an understanding of it
• Identifying differences in data distribution that could affect performance when deploying the model in the real world
• Verifying data quality, andoror ensuring it via data cleaning
• Supervising the data acquisition process if more data is needed
• Defining the preprocessing or feature engineering to be done on a given dataset
• Defining validation strategies
• Training models and tuning their hyperparameters
• Analyzing the errors of the model and designing strategies to overcome them
• Deploying models to production

Minimum Qualifications: What we are looking for:

• Bachelor's degree in Computer Science, Data Science, Mathematics, or a related field.
• 4+ years of experience in data science, machine learning, or related fields.
• Data Science or Machine Learning certifications (e.g., Google Professional Data Engineer, Microsoft Certified: Azure Data Scientist).
• Experience with specific data science platforms (e.g., AWS Sagemaker, Google AI Platform) is a plus.
  Willing to work in Jakarta Office
• Technical Skill Requirements:
• Proficiency in data science tools and languages (Python, R, SQL).
• Expertise in machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong knowledge of data processing, feature engineering, and model validation techniques.
• Experience with cloud platforms (e.g., AWS, GCP) and deployment of models to production.

Soft Skill Requirements:

• Strong problem-solving and analytical skills.
• Effective communication skills for presenting findings to stakeholders.
• Ability to work collaboratively in a team environment.
• Adaptability and a proactive approach to problem-solving.

The transaction is the lungs of the breathing economy, that is why our first step starts with a big dream to pave the way towards freedom of transaction. Since 2007, DOKU has been the first electronic payment system and risk management company in Indonesia. From paying and getting paid to transfer funds, all are possible with DOKU. For more than one decade, we have grown together alongside large and medium scaled companies to personal sellers from various lines of business, ranging from transportation, tourism, insurance, retail, donation, communities, and many more. Collaboration with partners such as local and international banks, also non-banking institutions has strengthened our reputation as a trusted local electronic payment solution. Our business grows together with our partners' businesses. Thus we have built a payment ecosystem that is supportive and strengthens theirs. The formation of three product pillars that responds to all business needs across all layers of society has marked our transformation from "The Better Way to Pay" becoming "Think Beyond Payments". The three winning product pillars comprise Payment Gateway and Transfer Services for Corporate, SMEs, Start-ups, and Local and International MSMEs. The last product pillar, Collaborative Commerce, is designed to empower communities and personal usage.

Company Introduction:

We exist to wow our customers. We know we're doing the right thing when we hear our customers say, "How did I ever live without Coupang?" Born out of an obsession to make shopping, eating, and living easier than ever, we're collectively disrupting the multi-billion-dollar commerce industry. We are one of the fastest-growing retail companies that established an unparalleled reputation for being a leading and reliable force in the commerce industry.

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. At Coupang, every day is filled with the excitement of building, you will see yourself, your colleagues, your team, and the company grow every day.

Our mission to build the future of commerce is real. We push the boundaries of what's possible to solve problems and challenge traditional tradeoffs. Join Coupang now to create an epic impact in this always-on, high-tech, and hyper-connected world.

Role Overview:

As a
Director, Data Science (Incrementality)
, you will be responsible for leveraging our tens of millions of data points to build ML products and intelligent algorithmic solutions - to facilitate scalable decisions and create WOW experience for our customers.

This is a rare opportunity to be part of a diverse, growing, and dynamic team with so much upward growth potential. You will be part of an early stage international expansion team where you will get a broad end-to-end view of aggressive expansion of an e-commerce business. For this reason, we are looking for a Director, Data Science who is comfortable working on end-to-end ML lifecycle from problem scoping all the way to ML deployment and post deployment experimentation.

What You Will Do:

• Understand business concerns and formulate them as technical problems that can be solved using data and math/stats/ML
• Work with product managers, machine learning engineers, and business users to build, deploy, and scale data science solutions
• Spearhead the technical excellence in data science and machine learning for the team
• Leveraging your experience in data science, machine learning, software engineering, distributed systems to rapidly prototype and deploy the systems to production
• Co-build data science culture as part of a growing data science team
• Independently design and conduct experiments to measure the impact of ML solutions or product features

Essential Qualifications

• Hands-on experience in statistics/ML fundamentals and demonstrated experience in Python, SQL, and basic visualization tools.
• Bachelor's/Master's degree in statistics, computer engineering or any other quantitative disciplines, with 10+ years of relevant experience
• Ability to write clear and concise technical documentation
• Strong critical thinking skills and ability to solve nonstructural problems supported by solid knowledge of data science and machine learning fundamentals, with proven experience to formulate business problems to data science solutions
• Expertise to conduct analysis independently for a business problem through data manipulation, formulation of hypotheses, design and statistical analysis of experiments to test them
• Experience with big data tools like Hadoop, Spark, and Presto

Preferred Qualifications:

• Experience with end-to-end ML lifecycle & integration of ML solution as a part of complex engineering system
• Proving track record of shipping an ML system
• Proving track record of delivering production grade operation research model is a plus
• Proficiency in writing clean code within version-controlled environments
• Experience working in e-commerce domain

Recruitment Process

• Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer
• The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances.
• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.

Details to Consider

• This job posting may be closed prior to the stated end date for application if all openings are filled.
• Coupang has the right to rescind an offer of employment if a candidate is found to have

submitted false information as part of the application process.

• Coupang does not discriminate against disabled applicants or those with veteran status.
• We are proud to offer equal opportunities for all applicants.

Privacy Notice

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice is located below.

Key Responsibilities :

• Develop, train, and optimize machine learning models for demand–supply prediction, route optimization, and customer/driver churn analysis.
• Implement predictive pipelines using structured and unstructured transportation data (GPS, sensor, transactional, behavioral).
• Collaborate with product and engineering teams to integrate ML models into production systems.
• Conduct exploratory data analysis (EDA) to identify key features, correlations, and anomalies in transportation datasets.
• Apply machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) to prototype and deploy AI models.
• Perform model validation, testing, and monitoring to ensure reliability and scalability in real-world use cases.
• Support data engineers in building scalable data pipelines and maintaining data quality.
• Document model design, performance metrics, and deployment processes for team knowledge sharing.

Requirements :

• Bachelor's degree in Computer Science, Data Science, Statistics, or related field.
• 3–5 years of experience in applied data science or machine learning engineering.
• Solid knowledge of supervised/unsupervised learning, regression, classification, clustering, and time-series forecasting.
• Hands-on experience in Python (pandas, scikit-learn, TensorFlow/PyTorch), SQL, and cloud environments (GCP/AWS/Azure).
• Familiarity with MLOps practices (CI/CD for ML, model versioning, monitoring).
• Strong problem-solving skills with ability to handle large-scale, imbalanced transportation datasets.
• Good communication skills to collaborate with cross-functional teams.

GroupM is the world's largest media investment company and a part of WPP. In fact, we are responsible for one in every three ads you see globally. We are currently looking for Manager. The role will be responsible to drive the development of digital marketing research as a form of service or product for clients as well as a tool to support the growth of digital business for GroupM agencies

Reporting of the role

This role reports to Mindshare Lead

3 best things about the job:

• Our ideal team member will have the mathematical and statistical expertise you'd expect.
• You will join a team of data specialists, but will "slice and dice" data using your own methods, creating new visions for the future.
• Insightful data to power our systems and solutions

In this role, your goals will be:

In three months:

• Communicate analytic solutions to stakeholders and implement improvements as needed to operational systems
• Implement analytical models into production by collaborating with software developers and machine learning engineers.

In six months:

• Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for uniformity and accuracy
• Analyse data for trends and patterns, and Interpret data with a clear objective in mind

In 12 months:

• Work as the lead data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the digital specialist team to strategize and execute the development of data products
• Execute analytical experiments methodically to help solve various problems and make a true impact across various domains and industries
• Identify relevant data sources and sets to mine for client business needs, and collect large structured and unstructured datasets and variables

What your day job looks like at Mindshare:

• Collaborate with connection planning and digital specialists to develop an understanding of needs
• Research and devise innovative statistical and machine learning models for data analysis

What you'll bring:

• Communicate findings to all stakeholders, using relevant data visualisations
• Enable smarter business processes—and implement analytics for meaningful insights
• Keep current with technical and industry developments

Minimum qualifications:

• Bachelor's degree in statistics, applied mathematics, or related discipline
• 5+ years' experience in data science
• Proficiency with data mining, mathematics, and statistical analysis
• Advanced pattern recognition, recommendation engines and predictive modelling experience
• Experience with Power BI, Tableau, SQL, and programming languages (i.e., Java/Python/R, SAS)
• Comfort working in a dynamic, research-oriented group with several ongoing concurrent projects

Job Title:
Data Science Engineer
About The Role:
To apply data science techniques and machine learning algorithms to solve business problems, improve decision-making, and ensure the efficient deployment of models in production.

What Will You Do:

• Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
• Analyzing the ML algorithms that could be used to solve a given problem
• Exploring and visualizing data to gain an understanding of it
• Identifying differences in data distribution that could affect performance when deploying the model in the real world
• Verifying data quality, andoror ensuring it via data cleaning
• Supervising the data acquisition process if more data is needed
• Defining the preprocessing or feature engineering to be done on a given dataset
• Defining validation strategies
• Training models and tuning their hyperparameters
• Analyzing the errors of the model and designing strategies to overcome them
• Deploying models to production

What we are looking for:

• Bachelor's degree in Computer Science, Data Science, Mathematics, or a related field.
• 4+ years of experience in data science, machine learning, or related fields.
• Data Science or Machine Learning certifications (e.g., Google Professional Data Engineer, Microsoft Certified: Azure Data Scientist).
• Experience with specific data science platforms (e.g., AWS Sagemaker, Google AI Platform) is a plus.

Soft Skill Requirements:

• Strong problem-solving and analytical skills.
• Effective communication skills for presenting findings to stakeholders.
• Ability to work collaboratively in a team environment.
• Adaptability and a proactive approach to problem-solving.

Technical Skill Requirements:

• Proficiency in data science tools and languages (Python, R, SQL).
• Expertise in machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong knowledge of data processing, feature engineering, and model validation techniques.
• Experience with cloud platforms (e.g., AWS, GCP) and deployment of models to production.

Company Description:

is a technology-driven health and life insurance provider in Indonesia, offering a holistic approach to healthcare services and well-being. Unlike traditional insurance products, Rey focuses on quality healthcare services to improve the lives of its members. The company is committed to reimagining and democratizing life and health insurance to make it more desirable and beneficial.

Responsibilities:

- Design, build, and evaluate prompts and agentic workflows for LLM - powered applications.

- Perform data analysis, feature engineering, and prototype machine learning models.- Contribute to our data pipelines, dbt models, and data quality testing frameworks.

- Colloborate with engineering, product, and business teams to deliver data products.

- Present findings and insights clearly to technical and non-technical audiences.

Requirements:

- Solid understanding of statistics, probability, and foundational machine learning concepts.

- Proficiency in Python for data science (pandas, scikit-learn) and SQL.

- A strong sense of ownership, curiosity, and a desire to learn in a fast-paced environment.- Excellent communication and collaboration skills.- (Preferred) Experience with LLMs, dbt, Airflow, Docker, or observability tools like Langfuse.

Job Type: Internship

Internship periode: 3 months

Job Title:

Data Science Engineer

About The Role:

To apply data science techniques and machine learning algorithms to solve business problems, improve decision-making, and ensure the efficient deployment of models in production.

What Will You Do:

• Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
• Analyzing the ML algorithms that could be used to solve a given problem
• Exploring and visualizing data to gain an understanding of it
• Identifying differences in data distribution that could affect performance when deploying the model in the real world
• Verifying data quality, andoror ensuring it via data cleaning
• Supervising the data acquisition process if more data is needed
• Defining the preprocessing or feature engineering to be done on a given dataset
• Defining validation strategies
• Training models and tuning their hyperparameters
• Analyzing the errors of the model and designing strategies to overcome them
• Deploying models to production

What we are looking for:

• Bachelor's degree in Computer Science, Data Science, Mathematics, or a related field.
• 4+ years of experience in data science, machine learning, or related fields.
• Data Science or Machine Learning certifications (e.g., Google Professional Data Engineer, Microsoft Certified: Azure Data Scientist).
• Experience with specific data science platforms (e.g., AWS Sagemaker, Google AI Platform) is a plus.

Soft Skill Requirements:

• Strong problem-solving and analytical skills.
• Effective communication skills for presenting findings to stakeholders.
• Ability to work collaboratively in a team environment.
• Adaptability and a proactive approach to problem-solving.

Technical Skill Requirements:

• Proficiency in data science tools and languages (Python, R, SQL).
• Expertise in machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong knowledge of data processing, feature engineering, and model validation techniques.
• Experience with cloud platforms (e.g., AWS, GCP) and deployment of models to production.