997 Data Mining jobs in Bahrain
Senior Data Scientist - Mining Operations
Posted 7 days ago
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Job Description
Key Responsibilities:
- Develop and implement machine learning models for predictive maintenance, operational optimization, and resource forecasting.
- Analyze large-scale datasets from exploration, production, and logistics to identify trends and anomalies.
- Design and build data pipelines for data collection, cleaning, and transformation.
- Collaborate with domain experts (geologists, engineers) to define analytical problems and solutions.
- Communicate complex analytical findings and recommendations to technical and non-technical stakeholders.
- Develop dashboards and visualizations to track key performance indicators (KPIs) and operational metrics.
- Stay abreast of the latest advancements in data science, machine learning, and AI relevant to the mining industry.
- Contribute to the development of data governance policies and best practices.
- Evaluate and implement new analytical tools and technologies.
- Mentor junior data scientists and analysts.
- Master's or Ph.D. in Data Science, Statistics, Computer Science, Operations Research, or a related quantitative field.
- Minimum of 7 years of experience as a Data Scientist, with a proven track record of delivering data-driven solutions.
- Strong proficiency in Python or R, including relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas, NumPy).
- Experience with big data technologies (e.g., Spark, Hadoop) and SQL.
- Familiarity with cloud computing platforms (AWS, Azure, GCP) and their data services.
- Knowledge of various machine learning algorithms (e.g., regression, classification, clustering, time series analysis, deep learning).
- Experience in the mining or natural resources sector is highly desirable.
- Excellent problem-solving, analytical, and critical-thinking skills.
- Strong communication and presentation skills.
- Ability to work independently and manage projects effectively in a remote setting.
Remote Data Scientist - Mining Operations
Posted 10 days ago
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Job Description
Responsibilities:
- Collect, clean, and preprocess large, complex datasets from various mining operations (e.g., geological data, sensor data, production logs, equipment performance data).
- Develop, implement, and validate predictive models to forecast resource yields, equipment failures, and operational risks.
- Design and execute statistical analyses to identify patterns, trends, and correlations within mining data.
- Build and deploy machine learning algorithms for applications such as optimizing drilling patterns, ore grade prediction, and energy consumption management.
- Visualize data and model results using advanced visualization tools to effectively communicate complex findings to technical and non-technical stakeholders.
- Collaborate closely with geologists, mining engineers, and operational managers to understand their data needs and challenges.
- Identify opportunities for data-driven improvements in safety, sustainability, and productivity.
- Stay current with the latest advancements in data science, machine learning, and their applications in the mining sector.
- Develop and maintain data pipelines and infrastructure to support analytical processes.
- Contribute to the development of data governance policies and best practices within the organization.
- Present findings and recommendations to senior management to influence strategic decisions.
- Master's or Ph.D. in Data Science, Statistics, Computer Science, Mining Engineering, or a related quantitative field.
- Proven experience (3-5+ years) as a Data Scientist, with a strong focus on applying analytical techniques to industrial or resource-based sectors.
- Demonstrated expertise in Python or R for data analysis and machine learning, including libraries like Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
- Experience with SQL and working with relational databases.
- Familiarity with big data technologies (e.g., Spark, Hadoop) is a plus.
- Strong understanding of statistical modeling, machine learning algorithms, and experimental design.
- Experience in the mining industry, including understanding of geological data, exploration techniques, or mine planning, is highly advantageous.
- Excellent data visualization skills (e.g., Matplotlib, Seaborn, Tableau).
- Strong problem-solving abilities and the capacity to translate business problems into analytical solutions.
- Excellent communication and presentation skills, with the ability to explain complex technical concepts to diverse audiences.
- Proven ability to work independently and manage projects effectively in a remote setting.
Senior Data Scientist - Mining Operations
Posted 22 days ago
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Job Description
Remote Lead Data Scientist - Mining Analytics
Posted 11 days ago
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Job Description
Responsibilities:
- Lead the development and implementation of advanced analytics solutions for mining operations, including predictive maintenance, process optimization, resource estimation, and safety analytics.
- Mentor and guide a team of data scientists, fostering a collaborative and high-performing environment.
- Collaborate with cross-functional teams to identify key business challenges and opportunities that can be addressed through data science.
- Design, build, and deploy machine learning models and statistical algorithms using large and complex datasets.
- Develop data pipelines, conduct feature engineering, and ensure the quality and integrity of data used for analysis.
- Communicate complex analytical findings and recommendations effectively to both technical and non-technical stakeholders through visualizations and presentations.
- Stay abreast of the latest advancements in data science, machine learning, and AI, and evaluate their applicability to mining operations.
- Contribute to the development of data governance strategies and best practices.
- Drive the adoption of data-driven decision-making across the organization.
- Manage project timelines, resources, and deliverables for data science initiatives.
Qualifications:
- Ph.D. or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
- 7+ years of experience in data science and machine learning, with at least 3 years in a leadership or senior role.
- Proven experience in applying data science techniques to solve complex problems in the mining, energy, or heavy industry sectors.
- Expertise in programming languages such as Python or R, and proficiency with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas).
- Strong understanding of statistical modeling, machine learning algorithms (supervised and unsupervised), and data mining techniques.
- Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP).
- Excellent communication, presentation, and stakeholder management skills.
- Ability to work independently and manage complex projects in a fully remote setting.
- Familiarity with geological data, sensor data, and operational data from mining contexts is highly desirable.
This is an exceptional remote opportunity to leverage cutting-edge data science to revolutionize the mining industry.
Remote Lead Data Scientist - Mining Analytics
Posted 12 days ago
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Job Description
Key Responsibilities:
- Lead the development and deployment of advanced analytical models and machine learning algorithms for mining applications.
- Design and implement data mining strategies to extract actionable insights from large, complex datasets.
- Develop predictive models for resource estimation, equipment failure prediction, operational efficiency, and safety risk assessment.
- Collaborate with domain experts (geologists, engineers) to define project requirements and interpret results.
- Build and maintain robust data pipelines and analytical workflows.
- Communicate complex findings and recommendations to stakeholders through clear visualizations and presentations.
- Mentor and guide junior data scientists and analysts.
- Stay current with the latest advancements in data science, machine learning, and AI.
- Contribute to the development of the company's data strategy and analytical roadmap.
- Ensure the ethical and responsible use of data.
Qualifications:
- Master's or Ph.D. in Data Science, Computer Science, Statistics, Operations Research, or a related quantitative field.
- Minimum of 7-10 years of experience in data science, with a significant focus on applying advanced analytics to industrial or resource-based sectors.
- Proven experience in developing and deploying machine learning models (e.g., regression, classification, clustering, deep learning).
- Strong proficiency in programming languages such as Python or R, and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience with big data technologies (e.g., Spark, Hadoop) and SQL.
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their data science services.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong leadership, communication, and presentation abilities.
- Knowledge of the mining industry or related resource sectors is highly desirable.
Remote Data Scientist - Mining Operations Optimization
Posted 13 days ago
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Job Description
Remote Principal Data Scientist - Mining Operations
Posted 15 days ago
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Job Description
- Developing and deploying sophisticated machine learning models for predictive maintenance, geological modeling, and operational optimization in mining environments.
- Leading data exploration, feature engineering, and model validation processes.
- Designing and implementing scalable data pipelines and analytical frameworks.
- Collaborating closely with geologists, mining engineers, and operational managers to identify key business challenges and opportunities.
- Mentoring junior data scientists and fostering a culture of innovation.
- Communicating complex findings and recommendations to both technical and non-technical stakeholders.
- Staying at the forefront of data science and AI advancements, particularly as they apply to the mining industry.
- Ensuring data integrity, security, and ethical usage.
- Contributing to the strategic direction of data analytics within the organization.
- Automating reporting and developing dashboards for key performance indicators.
A Ph.D. or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field is required, along with a minimum of 8 years of progressive experience in data science, with a significant portion focused on industrial or resource-based sectors. Proven experience in leading complex data science projects and a strong portfolio of successfully deployed models are essential. Expertise in Python or R, SQL, and experience with big data technologies (e.g., Spark) and cloud platforms (e.g., AWS, Azure, GCP) are mandatory. This remote role offers a highly competitive salary, comprehensive benefits, and the opportunity to make a substantial impact on the future of sustainable mining.
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Remote Geospatial Data Analyst - Mining Operations
Posted 16 days ago
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Job Description
Key Responsibilities:
- Acquire, process, and analyze diverse geospatial data, including but not limited to satellite imagery, aerial photography, LiDAR, and GPS data.
- Develop and implement advanced spatial analysis models to identify geological formations, mineral deposits, and exploration targets.
- Utilize GIS software (e.g., ArcGIS, QGIS) and remote sensing tools (e.g., ENVI, ERDAS Imagine) to create maps, reports, and visualizations.
- Integrate various data sources, including geological, geophysical, and geochemical data, into a unified geospatial framework.
- Conduct spatial statistics, trend analysis, and predictive modeling to support exploration and resource assessment.
- Monitor and assess environmental factors related to mining activities using remote sensing data.
- Collaborate with geologists, engineers, and other stakeholders to provide data-driven insights and recommendations.
- Develop automated workflows for data processing and analysis to enhance efficiency.
- Stay abreast of the latest advancements in geospatial technology and their potential applications in the mining industry.
- Prepare clear and concise technical reports and presentations for management and technical teams.
- Ensure data quality, accuracy, and integrity throughout the analysis process.
Required Qualifications:
- Master's degree or Ph.D. in Geospatial Science, Geography, Geology, Mining Engineering, or a related field with a strong focus on spatial analysis.
- Minimum of 5 years of professional experience in geospatial data analysis, preferably within the mining or natural resources sector.
- Proficiency in advanced GIS and remote sensing software (e.g., ArcGIS, QGIS, ENVI, ERDAS Imagine).
- Strong programming skills in Python or R for data manipulation and analysis (e.g., libraries like GeoPandas, Rasterio, NumPy).
- Experience with machine learning techniques applied to geospatial data is a significant advantage.
- Familiarity with geological and mining concepts.
- Excellent analytical, problem-solving, and critical thinking skills.
- Ability to work independently and manage multiple projects in a remote setting.
- Strong written and verbal communication skills for technical reporting and collaboration.
- Demonstrated ability to interpret complex spatial data and translate findings into actionable insights.
This is a unique opportunity to leverage your expertise in a challenging and rewarding field, contributing to the responsible development of natural resources from the comfort of your own home.
Senior Data Scientist - Mining & Geospatial Analysis (Remote)
Posted 19 days ago
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Job Description
Key Responsibilities:
- Develop and implement advanced statistical and machine learning models for mineral exploration, resource estimation, and operational efficiency.
- Analyze and interpret large-scale geological, geophysical, and geospatial datasets.
- Design and build data pipelines for collecting, cleaning, and transforming diverse data sources.
- Create compelling data visualizations and dashboards to communicate insights to stakeholders.
- Collaborate with geologists, engineers, and operational teams to define data-driven strategies.
- Conduct predictive modeling to forecast production, identify risks, and optimize resource allocation.
- Stay current with the latest advancements in data science, AI, and their applications in the mining sector.
- Evaluate and implement new data analysis tools and technologies.
- Develop and maintain documentation for data models, algorithms, and methodologies.
- Mentor junior data scientists and contribute to the team's technical growth.
Qualifications:
- Master's or Ph.D. in Data Science, Statistics, Computer Science, Geophysics, or a related quantitative field.
- Minimum of 6-8 years of experience in data science, with a significant focus on the mining or natural resources sector.
- Proven expertise in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and experimental design.
- Strong proficiency in programming languages such as Python or R, and experience with libraries like Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
- Experience with geospatial analysis tools and techniques (e.g., ArcGIS, QGIS, spatial statistics).
- Familiarity with cloud platforms (AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop).
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and presentation skills, with the ability to explain complex technical concepts to non-technical audiences.
- Proven ability to work independently and manage projects effectively in a remote setting.
- Experience with data relevant to the operations in the Manama, Capital, BH region is advantageous, but the role is fully remote.
Remote Lead Data Scientist - Mining Operations Analytics
Posted 22 days ago
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Job Description
- Leading the design, development, and implementation of data science solutions for mining operations.
- Building and maintaining advanced machine learning models for predictive analytics (e.g., yield prediction, equipment failure, safety risks).
- Developing data pipelines and ETL processes for large, complex datasets from various sources.
- Collaborating with domain experts to define business problems and translate them into analytical frameworks.
- Mentoring and guiding junior data scientists and analysts.
- Communicating complex analytical findings and recommendations to diverse stakeholders.
- Staying abreast of the latest advancements in data science, AI, and machine learning.
- Ensuring the ethical and responsible use of data.
- Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
- Minimum of 7 years of experience as a Data Scientist, with at least 2 years in a lead or senior role.
- Proven experience in applying machine learning and statistical modeling to solve complex business problems.
- Proficiency in Python or R, and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas).
- Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP) is highly desirable.
- Strong understanding of geological data, mining processes, and operational challenges.
- Excellent problem-solving, analytical, and critical thinking skills.
- Exceptional communication and leadership abilities.