2,968 Exploratory Data Analysis jobs in Kenya

• Interpret and analyze diverse geological data sets (geophysical, well logs, seismic).
• Develop geological models and resource estimations.
• Identify and evaluate potential mineral or hydrocarbon deposits.
• Provide geological guidance for exploration and drilling programs.
• Prepare comprehensive geological reports and presentations.
• Assess geological risks and uncertainties.
• Collaborate with exploration and engineering teams.
• Utilize advanced geological modeling and interpretation software.
• Stay abreast of geological research and industry best practices.
• Contribute to strategic exploration planning.

• Master's degree or PhD in Geology, Geophysics, or a related field.
• Minimum of 8 years of experience in geological interpretation and exploration.
• Proven expertise in analyzing geophysical, seismic, and well log data.
• Proficiency with geological modeling software (e.g., Petrel, Leapfrog, ArcGIS).
• Strong understanding of structural geology, stratigraphy, and sedimentology.
• Excellent analytical and problem-solving skills.
• Effective written and verbal communication abilities.
• Experience working independently in a remote environment.
• Familiarity with resource estimation techniques.
• Ability to manage multiple projects and meet deadlines.

A Business Data Analytics and Research intern plays a crucial role in organizations by leveraging data to drive strategic decision-making, conducting research to identify market trends, and optimizing business operations. Below are key responsibilities and skills typically associated with this role:

Key Responsibilities:

1. Data Collection and Analysis
   :

2. Gather and analyze business, market, and financial data from various sources to provide insights into performance and trends.

3. Use statistical tools to interpret data sets, identifying patterns and trends that inform business decisions.

2.Data Visualization, Reporting and Presentation
:

• Prepare and present detailed reports, dashboards, and visualizations that summarize key data insights and findings.
• Communicate complex data results to non-technical stakeholders in a clear and actionable manner.
• Capacity to develop concept notes and proposals based on market research gaps

3. Market Research
:

• Conduct qualitative and quantitative research to identify new market opportunities, competitor analysis, and customer preferences.
• Evaluate market conditions, industry trends, and competitors' activities to support business growth strategies.
• Prepare presentations based on market research reports

4.Business Performance Monitoring
:

• Monitor key performance indicators (KPIs) to track business progress and identify areas for improvement.
• Recommend improvements based on data insights to optimize processes, reduce costs, and increase profitability.

5.Collaborating with Teams
:

• Work closely with different departments such as marketing, finance, and operations to align data-driven insights with business objectives.
• Provide support for product development, sales strategies, and customer experience initiatives through data analysis.

6.Data Management
:

• Ensure the accuracy, completeness, and security of data.
• Develop and maintain databases, data collection systems, and strategies for efficient data storage and retrieval.

Key Skills:

1.Data Analytics Tools
:

• Proficient in tools like SQL, Excel, Tableau, Power BI, Google Analytics, and other business intelligence platforms.

2.Statistical Analysis
:

• Knowledge of statistical software (e.g., R, SAS, SPSS) and techniques such as regression analysis, hypothesis testing, and predictive modeling.

3.Research and Excellent Writing skills:

• Strong ability to conduct both primary and secondary research, including surveys, interviews, and literature reviews.
• Capacity to develop report and concepts based on market research reports

4.Problem-Solving
:

• Analytical thinking to identify issues, trends, and opportunities through data, and propose actionable solutions.

5.Communication Skills
:

• Excellent written and verbal communication skills to present findings and recommendations clearly to stakeholders.

6.Attention to Detail
:

• High level of precision in handling large data sets and ensuring data accuracy.

7.Project Management
:

• Ability to manage multiple research projects simultaneously, ensuring timely delivery of results.

Education, knowledge and experience:

• A degree in Agricultural Economics or a related field.
• Experience in management and analysis of data.
• Field experience and synthesis of data and lessons for learning
• Knowledge and savvy of data analysis software, especially Stata.
• Very strong analytical skills and applied statistical experience.
• Good scientific wring experience.

• Leading the design, development, and implementation of advanced machine learning models and algorithms.
• Conducting in-depth data analysis, feature engineering, and model evaluation on large, complex datasets.
• Researching and exploring new ML techniques and technologies to solve challenging business problems.
• Developing and deploying robust, scalable ML solutions into production environments.
• Mentoring junior data scientists and contributing to the growth of the data science team.
• Collaborating with cross-functional teams to understand business needs and translate them into data science projects.
• Communicating complex findings and model insights to technical and non-technical stakeholders.
• Staying abreast of the latest advancements in machine learning, AI, and related fields.
• Designing and executing experiments to validate hypotheses and improve model performance.
• Developing and maintaining clear documentation for models, code, and methodologies.
• Contributing to the company's intellectual property through publications and patents.
• Ensuring the ethical and responsible development and deployment of AI systems.
• Building and maintaining data pipelines for model training and inference.
• Proactively identifying opportunities for leveraging data science to drive business value.
• Championing data-driven approaches throughout the organization.

• Assist in collecting and organizing data from various internal and external sources, including surveys, databases, and public records.
• Perform data cleaning and preprocessing tasks to ensure data accuracy and integrity.
• Conduct preliminary data analysis using statistical methods and software tools.
• Help generate reports and visualizations to present data findings to the team.
• Support senior analysts in developing market research methodologies and survey instruments.
• Identify trends, patterns, and anomalies within datasets and flag them for further investigation.
• Learn and apply new analytical techniques and tools as required.
• Contribute to the documentation of data sources, methodologies, and findings.
• Collaborate with team members remotely to discuss project progress and findings.
• Assist in preparing presentations summarizing research insights.

• Currently pursuing or recently completed a Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Business Analytics, or a related quantitative field.
• Foundational understanding of statistical concepts and data analysis principles.
• Familiarity with data analysis tools such as Excel, and basic knowledge of SQL, Python, or R is a plus.
• Strong analytical and problem-solving skills with a high level of attention to detail.
• Excellent written and verbal communication skills, with the ability to clearly articulate findings.
• Ability to work independently and manage time effectively in a remote environment.
• Eagerness to learn and adapt to new technologies and methodologies.
• A genuine interest in market research and data-driven decision-making.
• Proactive and able to take initiative on assigned tasks.

• Design, develop, and implement sophisticated machine learning models and algorithms to solve complex business problems.
• Conduct exploratory data analysis to identify patterns, trends, and insights from large and complex datasets.
• Perform feature engineering, model selection, training, validation, and hyperparameter tuning.
• Develop predictive and prescriptive models for applications such as forecasting, anomaly detection, recommendation systems, and natural language processing.
• Evaluate model performance, interpret results, and communicate findings clearly to technical and non-technical stakeholders.
• Collaborate with software engineers to deploy machine learning models into production environments.
• Stay abreast of the latest research and advancements in machine learning, AI, and related fields.
• Design and conduct experiments to test hypotheses and validate model effectiveness.
• Develop and maintain robust data pipelines for model training and inference.
• Mentor junior data scientists and contribute to the team's technical growth.
• Ensure data quality, integrity, and privacy throughout the data science lifecycle.
• Write clean, well-documented, and reproducible code, primarily in Python or R.
• Contribute to the development of intellectual property through research and innovation.

• Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field with a focus on Machine Learning.
• Proven track record of conducting cutting-edge research and developing impactful machine learning models.
• Extensive experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong programming skills in Python or R, including experience with data manipulation libraries (e.g., Pandas, NumPy).
• Proficiency in SQL and experience working with various database systems.
• Deep understanding of statistical concepts, algorithms, and their practical application.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Excellent analytical, problem-solving, and critical thinking skills.
• Superior communication and presentation skills, capable of explaining complex technical concepts to diverse audiences remotely.
• Ability to work independently, manage projects, and drive research initiatives from conception to completion.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) for machine learning is beneficial.

• Assist in the collection, cleaning, and preprocessing of diverse datasets from various sources.
• Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies.
• Develop and implement basic machine learning models under the guidance of senior team members.
• Visualize data and model results using tools such as Python libraries (Matplotlib, Seaborn) or Tableau.
• Collaborate with data scientists and engineers on feature engineering and model selection.
• Document methodologies, findings, and code for reproducibility and knowledge sharing.
• Participate in regular team meetings and contribute to project discussions.
• Learn and apply new data analysis techniques and tools relevant to AI/ML.
• Assist in the testing and validation of AI/ML models.
• Contribute to the overall data strategy and innovation efforts.

• Recent graduate with a Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative field.
• Foundational understanding of statistical concepts and data analysis techniques.
• Basic programming skills in Python or R, including experience with relevant data manipulation and analysis libraries (e.g., Pandas, NumPy).
• Familiarity with machine learning concepts and algorithms is highly desirable.
• Exposure to data visualization tools.
• Strong analytical and problem-solving abilities.
• Excellent communication and teamwork skills, essential for remote collaboration.
• Proactive attitude and eagerness to learn and take on new challenges.
• Self-motivated and able to manage tasks effectively in a remote environment.
• A genuine interest in AI and Machine Learning.

• Assist in data collection, cleaning, and preprocessing.
• Perform descriptive statistical analysis and generate basic reports.
• Create data visualizations to illustrate findings and trends.
• Conduct literature searches and summarize research findings.
• Support senior team members in data-driven projects.
• Maintain organized and accurate data records.
• Collaborate effectively with remote team members.
• Contribute to the development of research methodologies.
• Learn and apply new data analysis techniques and tools.

• Currently pursuing or recently completed a degree in Statistics, Mathematics, Economics, Computer Science, or a related field.
• Strong analytical and quantitative skills.
• Proficiency in Microsoft Excel for data analysis.
• Familiarity with statistical software (e.g., R, Python) is a plus.
• Excellent attention to detail and accuracy.
• Strong written and verbal communication skills for remote interaction.
• Ability to work independently and manage workload in a remote setting.
• Eagerness to learn and develop data analysis skills.
• Passion for research and problem-solving.