16 Data Entry Roles jobs in Manama

• Assist in the collection, cleaning, and processing of large datasets from various sources.
• Perform basic data analysis to identify trends, patterns, and anomalies.
• Create clear and concise reports and visualizations to communicate findings to stakeholders.
• Collaborate with senior analysts and data scientists on ongoing projects.
• Develop and maintain data dictionaries and documentation.
• Support the development and implementation of data quality checks.
• Gain exposure to statistical modeling and predictive analytics techniques.
• Participate in team meetings and contribute to brainstorming sessions.
• Learn and apply best practices in data management and analysis.
• Proactively identify opportunities for process improvement within data handling.

• Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
• Strong analytical and problem-solving skills.
• Proficiency in at least one data analysis tool or programming language (e.g., Python, R, SQL, Excel).
• Excellent communication and presentation skills, with the ability to explain technical concepts to non-technical audiences.
• Detail-oriented with a commitment to accuracy.
• Ability to work independently and manage time effectively in a remote setting.
• Eagerness to learn and adapt to new technologies and methodologies.
• Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus.
• A genuine passion for data and its potential to drive business value.
• Must be legally authorized to work remotely.

• Structured training program covering data analysis fundamentals, SQL, Excel, and data visualization tools (e.g., Tableau, Power BI).
• Mentorship from senior data analysts, providing guidance and support throughout the apprenticeship.
• Practical experience working on real-world data projects.
• Learning to clean, transform, and analyze large datasets to identify trends and patterns.
• Developing skills in creating compelling data visualizations and reports.
• Exposure to different analytical techniques and statistical concepts.
• Opportunities to collaborate with team members on data-driven initiatives in a remote setting.
• Development of critical thinking, problem-solving, and communication skills.
• Clear learning objectives and performance evaluations to track progress.
• Potential for conversion to a full-time Data Analyst role upon successful completion of the apprenticeship.
• Access to online learning resources and collaborative project management tools.
• Understanding of data governance and best practices.

• Recent graduate with a degree in Statistics, Mathematics, Economics, Computer Science, Business, or a related quantitative field, or individuals with demonstrable analytical skills.
• Strong foundation in mathematical and statistical concepts.
• Excellent logical reasoning and problem-solving abilities.
• Detail-oriented with a commitment to accuracy.
• Proficiency in Microsoft Excel or Google Sheets is essential.
• Basic understanding of database concepts and SQL is a plus.
• Enthusiasm for learning data analysis tools and techniques.
• Good written and verbal communication skills, capable of explaining findings.
• Self-motivated and able to manage time effectively in a remote work environment.
• A proactive attitude towards learning and skill development.
• Ability to work collaboratively in a virtual team.

• Assist in data collection, cleaning, and pre-processing from various sources.
• Perform exploratory data analysis to identify trends, patterns, and anomalies.
• Support the development of reports, dashboards, and visualizations using tools like Power BI or Tableau.
• Collaborate with senior analysts to interpret data and formulate actionable recommendations.
• Conduct market research and competitive analysis to inform business strategy.
• Participate in team meetings, contributing ideas and sharing findings.
• Learn and apply statistical methods and data modeling techniques.
• Maintain data integrity and documentation for all analytical processes.
• Engage in continuous learning to stay updated with the latest data analytics tools and methodologies.
• Contribute to ad-hoc data requests from various departments.

• Bachelor's degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or a related discipline.
• Strong analytical and problem-solving skills with a keen attention to detail.
• Basic understanding of statistical concepts and data analysis principles.
• Familiarity with spreadsheet software (e.g., Microsoft Excel) for data manipulation and analysis.
• Excellent written and verbal communication skills.
• Ability to work collaboratively in a team environment.
• Proactive and eager to learn new technologies and methodologies.
• Prior internship or project experience in data analysis is a plus, but not required.

Main Tasks:

1. Operate and maintain the On-Premises and co-located data center and related facilities.
2. Keep track of all Company Data Center facilities, assets, equipment, installations, access control systems, fire suppression systems, etc.
3. Implement and execute the necessary Data Center facility development, maintenance, support, and operation.
4. Continuously monitor Data Center facilities, power and cooling (HVAC), security access control, compute, storage, network and telecommunications equipment and services, system logs and alerts.
5. Carry on preventative and planned/unplanned maintenance activities of Data Center resources.
6. Coordinate all faulty hardware replacement, capacity expansion, server installation, decommissioning with internal technical teams, vendors, partners, and external customers.
7. Manage the installation of pre-integrated racks, individual servers and network appliances including stacking, wiring, cable managing and equipment labeling.
8. Ensure all necessary operational arrangements are in place to maintain and recover the Data Center facilities and services in the event of a disaster or major unplanned outage, as per approved Business Continuity Plan (BCP).
9. Work closely with approved service providers, maintain accurate Data Center configuration and operation documentation, update timely and accurately relevant documentation and diagrams.
10. 24 hours On-Call to provide urgent support especially on continuous operation that affects the company’s production.
11. Follow the internal General Data Center Guidelines.

Certification:

• Bachelor's degree in computer science or equivalent.
• Minimum three (3) years of hands-on experience in the same field.
• Mandatory requirement: Car plus driver license.

Interested candidates can email their CVs to .

• Analyze agricultural data, including soil health, climate patterns, crop growth, pest infestation, and irrigation needs.
• Develop and implement data-driven strategies to optimize planting, fertilization, pest control, and harvesting processes.
• Utilize remote sensing technologies, GIS, and IoT devices to monitor crop health and field conditions.
• Provide expert advice and recommendations to farmers and agricultural stakeholders on best practices and technological adoption.
• Design and manage databases for agricultural research and operational data.
• Create predictive models for yield forecasting, disease outbreaks, and weather-related risks.
• Evaluate and recommend new agricultural technologies, software, and equipment.
• Develop training materials and conduct virtual workshops on agricultural technology and data utilization.
• Collaborate with agronomists, researchers, and farm managers to integrate data insights into practical applications.
• Monitor environmental impacts and contribute to the development of sustainable farming solutions.
• Ensure data accuracy, integrity, and security for all agricultural information.
• Prepare comprehensive reports and presentations on findings, trends, and recommendations for stakeholders.
• Stay updated on the latest advancements in agricultural science, technology, and data analytics.
• Assist in the development of grant proposals and research projects related to agricultural innovation.

• Bachelor's degree in Agricultural Science, Agronomy, Data Science, Computer Science, or a related field. Master's degree preferred.
• Minimum of 4-6 years of experience in agricultural technology, data analysis, or a related role within the agriculture sector.
• Proven experience with agricultural data analysis tools, GIS software, and IoT platforms.
• Strong programming skills in languages like Python or R for data analysis and modeling.
• Familiarity with remote sensing, precision agriculture techniques, and farm management software.
• Excellent understanding of plant science, soil science, and agronomy principles.
• Exceptional analytical, problem-solving, and critical thinking skills.
• Strong written and verbal communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Ability to work independently, manage projects, and meet deadlines in a remote setting.
• Passion for sustainable agriculture and technological innovation.
• Experience with statistical software and data visualization tools is highly desirable.

• Design and implement data mining strategies to uncover trends, patterns, and correlations in large datasets.
• Develop and validate predictive models using machine learning algorithms and statistical methods.
• Clean, preprocess, and transform raw data to prepare it for analysis.
• Evaluate the performance of data mining models and refine them for optimal accuracy and efficiency.
• Collaborate with business stakeholders to understand their needs and translate them into data mining objectives.
• Visualize and present complex data insights in a clear and understandable manner to technical and non-technical audiences.
• Stay abreast of the latest advancements in data mining, machine learning, and artificial intelligence.
• Develop and maintain documentation for data mining processes and methodologies.
• Identify opportunities to improve data collection and management processes.
• Troubleshoot and resolve data-related issues.

• Master's degree or Ph.D. in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
• Minimum of 5 years of professional experience in data mining, machine learning, or statistical analysis.
• Proven expertise in programming languages such as Python or R, and proficiency with relevant libraries (e.g., scikit-learn, TensorFlow, Pandas).
• Strong understanding of various data mining techniques (e.g., classification, regression, clustering, association rule mining).
• Experience with database management and SQL.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and presentation skills, with the ability to explain technical concepts to diverse audiences.
• Ability to work effectively in a team environment and independently manage assigned tasks.
• Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus.
• Experience in the mining sector is highly advantageous.

Job Objectives

Responsible for designing, developing, and deploying advanced analytics models to solve business problems. This role requires strong expertise in coding, statistical analysis, machine learning, and data visualization, with the ability to communicate insights effectively to both technical and non-technical stakeholders.

• Collect, clean, and process structured and unstructured data from multiple sources.
• Develop predictive and prescriptive models using advanced machine learning and statistical techniques.
• Apply natural language processing (NLP), computer vision, or deep learning where relevant.
• Collaborate with cross-functional teams (IT, Business, and Product) to define data-driven solutions.
• Deploy models into production environments and monitor performance.
• Design dashboards and reports to communicate findings and recommendations.
• Ensure compliance with data governance, security, and privacy policies.
• Stay updated with emerging tools, frameworks, and trends in AI/ML.

• Master's degree in Data Science
• Bachelor’s degree in Computer Science, Computer Engineering, Statistics, Data Science, Mathematics, Actuarial Science

• 4-7 years of hands-on experience in data analytics, business intelligence, business analytics, data science, and machine learning.
• Proficiency in Python/R and SQL with good knowledge of cloud platforms.

• Lead the process of identifying, analyzing, and resolving data quality issues across multiple databases and platforms.
• Develop and execute data cleansing scripts and routines using various tools and programming languages (e.g., SQL, Python).
• Implement data validation rules and checks to prevent future data integrity problems.
• Perform root cause analysis for data errors and work with relevant teams to implement preventive measures.
• Create and maintain comprehensive documentation for data cleansing processes, methodologies, and standards.
• Mentor and guide junior data specialists in best practices for data sanitation.
• Collaborate with data engineers, analysts, and business stakeholders to understand data requirements and ensure data accuracy.
• Monitor data quality metrics and provide regular reports on data health and cleansing progress.
• Develop and implement strategies for data standardization and harmonization across disparate data sources.
• Stay up-to-date with emerging trends and technologies in data management and quality assurance.
• Contribute to the design and implementation of data governance frameworks.
• Proactively identify opportunities for process improvement in data handling and quality control.
• Ensure compliance with data privacy regulations and internal policies.

• Bachelor's degree in Computer Science, Information Technology, Statistics, or a related quantitative field.
• Minimum of 5 years of experience in data management, data quality, or data cleansing roles.
• Proficiency in SQL for data manipulation and querying is essential.
• Experience with programming languages such as Python for data analysis and scripting.
• Strong understanding of database structures, data modeling, and data warehousing concepts.
• Proven ability to identify, analyze, and resolve complex data quality issues.
• Experience with data quality tools and techniques.
• Excellent analytical and problem-solving skills with a keen attention to detail.
• Strong written and verbal communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Ability to work independently, manage multiple priorities, and meet deadlines in a remote work environment.
• Experience with cloud data platforms (e.g., AWS, Azure, GCP) is a plus.
• Familiarity with data governance principles and practices is beneficial.

Job purpose

• Overseeing information security, cybersecurity and IT risk management programs based on industry-accepted information security and risk management frameworks.
• Responsible for the organization's data privacy and protection function to ensure compliance with various regulations and best practices.

2. Primary Duties Performed

• Develop and maintain the cybersecurity Risk Management Framework of the organization for addressing the overall approach for handling cybersecurity risks and managing them in a methodological manner.

• Evaluate employees' information security awareness and provide the necessary training whenever is needed.

• Conduct frequent reviews on Vulnerability Assessment and Penetration Testing (VAPT) and manage vulnerabilities.

• Define the necessary controls to ensure all regulatory requirements related to cybersecurity are met, designed effectively with clear documentation.

• Identify the critical assets of the organization and ensure implementation of risk identification and management strategies for these critical assets.
• To assess technology projects to ensure that cybersecurity is adequately addressed.
• Responsible to identifying and managing cybersecurity risk for all third-party technology engagements and all cloud computing engagements.
• Evaluates and recommends cybersecurity technologies and solutions.
• Review cybersecurity & Risk Management manual and recommend necessary updates.
• Act as Data Protection Officer to identify and evaluate the Company's data processing activities.
• Monitor data management procedures and compliance within the Company.
• Assess Company compliance with Data Protection Private Law.
• Provide advice and arrange training to employees on Data Protection.
• Review and recommend updates on Data Protection Manual.
• Serve as the point of contact between the company and the data protection authorities.
• Performs other related duties assigned by the department head.

3. Secondary Duties Performed

• Assist in implementing risk management framework, policies and programs covering business, financial, operational, technological, and regulatory risks.
• Assist in the development and management of controls and business contingency plans.
• Maintain and update organizational risk register.
• Oversee the regular validation and testing of the Company Business Continuity Plan.
• Review Risk Management manual and recommend necessary updates.

4. Work & Business Contacts

Internal

• Management team and staff.

External

• Regulatory Bodies: Central Bank of Bahrain and Personal Data Protection Authority.
• Law Firms and Legal Advisors.
• Internal and External Auditors.
• VAPT vendors.

Division / Department: Risk Management

Incumbent Reports to: Manager – Risk & Project Management