372 Big Data jobs in Indonesia

• Lead the development and implementation of advanced machine learning models and algorithms.
• Design, build, and maintain scalable data pipelines for large-scale data processing.
• Extract, transform, and analyze complex datasets to identify trends and patterns.
• Develop predictive models to forecast business outcomes and optimize operations.
• Communicate findings, insights, and recommendations to senior management and cross-functional teams.
• Collaborate with engineering teams to deploy machine learning models into production environments.
• Mentor and guide junior data scientists, fostering a culture of technical excellence.
• Stay abreast of the latest advancements in data science, AI, and machine learning.
• Define data strategy and roadmap for the organization.

• Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• 10+ years of experience in data science, machine learning, and big data analytics.
• Expertise in Python or R, with proficiency in relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Hands-on experience with big data technologies such as Apache Spark, Hadoop, and distributed computing.
• Proficiency in SQL and experience with various database systems.
• Experience with cloud platforms (AWS, Azure, GCP) and their data services.
• Strong understanding of statistical modeling, experimental design, and A/B testing.
• Excellent communication, presentation, and storytelling skills.
• Proven ability to lead complex projects and mentor team members.

• Assist in data extraction, transformation, and loading (ETL) processes from various data sources.
• Perform data cleaning, validation, and preprocessing to ensure data quality and integrity.
• Conduct exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
• Support the development and implementation of statistical and machine learning models.
• Assist in building visualizations and dashboards to communicate data insights.
• Collaborate with senior data scientists on various analytical projects.
• Write and optimize SQL queries for data retrieval and manipulation.
• Contribute to the documentation of data processes, methodologies, and findings.
• Stay updated with emerging trends and techniques in data science and big data analytics.
• Participate in team meetings and contribute to project discussions.

• Currently pursuing or recently completed a Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Foundational knowledge of statistics and probability.
• Proficiency in Python or R, including experience with data manipulation libraries (e.g., Pandas, NumPy, dplyr).
• Familiarity with SQL for database querying.
• Basic understanding of machine learning concepts.
• Strong analytical and problem-solving skills.
• Excellent attention to detail.
• Ability to work independently and manage time effectively in a remote environment.
• Good written and verbal communication skills.
• Eagerness to learn and develop new skills in data science.

• Assist in the collection, cleaning, and preprocessing of large datasets from various sources.
• Support the development and implementation of machine learning models and algorithms under the guidance of senior data scientists.
• Conduct exploratory data analysis to identify patterns, trends, and anomalies.
• Help in the visualization of data and model results using tools like Python libraries (Matplotlib, Seaborn) or R packages.
• Collaborate with the data engineering team to ensure data quality and accessibility.
• Participate in team meetings, contributing ideas and insights to ongoing projects.
• Assist in the documentation of data science processes, methodologies, and findings.
• Learn and apply various data mining techniques and statistical methods.
• Gain exposure to big data technologies and cloud platforms.
• Contribute to ad-hoc data analysis requests from different business units.
• Research and evaluate new data science tools and techniques.
• Develop basic dashboards and reports to communicate key metrics.

• Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
• Proficiency in programming languages such as Python or R, including relevant data science libraries (e.g., Pandas, NumPy, Scikit-learn).
• Basic understanding of statistical concepts and machine learning algorithms.
• Familiarity with SQL for database querying.
• Strong analytical and problem-solving skills.
• Excellent communication and interpersonal skills, with the ability to explain technical concepts to non-technical audiences.
• Eagerness to learn and adapt in a fast-paced environment.
• Ability to work effectively both independently and as part of a team.
• Prior experience with data visualization tools is a plus.
• Understanding of big data technologies (e.g., Spark, Hadoop) is beneficial but not required.

Jobdesc:

• Implementation and maintenance Bigdata Platform Cloudera

Requirements:

• Bachelor's degree in Information Systems or related field.
• At least 1 year experience in Cloudera administration.
• Knowledge and experience of SQL Query, NoSQL database Shell scripting and Python Scripts is a must.
• Understanding linux OS platform is a must, with experience in Red Hat being a plus.
• Familiarity with big data tools and frameworks, including Spark, HBase, Hive, and Hadoop.
• Experience with Cloudera is a plus.
• Familiarity with NiFi.
• Excellent troubleshooting skills.
• Strong communication skills and the ability to work effectively in a team.

• Assist in collecting, cleaning, and preprocessing large datasets.
• Perform exploratory data analysis to identify patterns and insights.
• Develop and implement machine learning models under supervision.
• Create data visualizations to communicate findings effectively.
• Collaborate with senior data scientists on analytical projects.
• Assist in evaluating model performance and iterating on solutions.
• Contribute to documentation of data analysis processes and findings.
• Learn and apply statistical techniques and data mining methods.
• Participate in team meetings and contribute to project discussions.
• Manage assigned tasks and communicate progress in a remote environment.

• Pursuing or recently completed a Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Proficiency in programming languages commonly used in data science, such as Python or R.
• Understanding of statistical concepts and machine learning algorithms.
• Familiarity with data manipulation and analysis libraries (e.g., Pandas, NumPy).
• Basic knowledge of data visualization tools.
• Strong analytical and problem-solving skills.
• Excellent communication skills, with the ability to explain technical concepts to a non-technical audience.
• Ability to work independently and manage time effectively in a remote setting.
• Eagerness to learn and apply new data science techniques.

Job Responsibilities

• Lead and oversee Big Data initiatives, ensuring alignment with corporate digital transformation and business strategies.
• Manage end-to-end project lifecycle: planning, resource allocation, execution, monitoring, risk management, and delivery within agreed timeline and budget.
• Collaborate with cross-functional teams (IT, Data Engineering, Business Units, External Vendors) to translate business needs into Big Data solutions.
• Define project scope, objectives, deliverables, and KPIs to measure success and ensure business value realization.
• Ensure compliance with IT governance, data security, and data privacy standards.
• Monitor project progress, anticipate issues, and proactively resolve risks and conflicts.
• Act as the primary liaison for stakeholders, providing regular updates, reports, and presentations to management and executives.
• Drive adoption of best practices in project management and Big Data implementation across the organization.

Requirements

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, or related field.
• Minimum 5–7 years of proven experience in Project Management, with at least 3 years handling Big Data or Analytics-related projects.
• Strong knowledge of Big Data technologies and ecosystem: Hadoop, Spark, Kafka, Hive, Cloud Data Platforms (AWS, GCP, or Azure).
• Experience in managing large-scale data integration, ETL pipelines, data warehouse, or data lake projects.
• Familiarity with data governance frameworks, compliance, and security practices.
• Solid understanding of Agile, Scrum, or Hybrid project methodologies.
• Excellent leadership, stakeholder management, and communication skills, with ability to influence both technical and non-technical stakeholders.
• Strong analytical, problem-solving, and decision-making abilities.
• Professional certification such as PMP, PRINCE2, or Agile/Scrum Master is an advantage.
• Automotive industry or large enterprise experience will be a strong plus.

Job Title:
Technical Analyst

Location:
 Jakarta

Experience:
 5+ Years

Industry:
 Banking/Financial Services

Job Description:

We are seeking a skilled 
Technical Analyst
 with strong experience in the 
banking domain
 to join our team. The ideal candidate will have expertise in 
PL/SQL, Cloudera, and Big Data technologies
, along with hands-on experience in 
banking-related projects
.

Key Responsibilities:

• Analyze and translate business requirements into technical solutions in the banking sector.
• Develop, optimize, and maintain 
  PL/SQL
   queries, stored procedures, and database solutions.
• Work with 
  Cloudera/Hadoop ecosystem
   for Big Data processing, analytics, and reporting.
• Collaborate with cross-functional teams to deliver data-driven solutions for banking projects.

Required Skills & Qualifications:

• 5+ years of experience
   in the 
  banking/financial services domain
  .
• Strong expertise in 
  PL/SQL
   (writing complex queries, stored procedures, performance tuning).
• Hands-on experience with 
  Cloudera, Hadoop, Hive, Spark, or related Big Data technologies
  .
• Knowledge of data warehousing, ETL processes, and data modeling in banking contexts.
• Familiarity with regulatory and compliance standards in banking (e.g., Basel, AML, KYC).
• Experience in Agile/Scrum methodologies is a plus.
• Strong analytical and problem-solving skills.

Education:

• Bachelor's or Master's degree in 
  Computer Science, IT, or related field
  .