179 Junior Data Lead jobs in Bahrain

Since 2011, General Assembly has transformed tens of thousands of careers through pioneering, experiential education in today's most in-demand skills. As featured in The Economist, Wired, and The New York Times, GA offers training in web development, data, design, business, and more, both online and at campuses around the world. Our global professional community boasts 60,000 full- and part-time alumni — and counting. In addition to fostering career growth for individuals, GA helps employers cultivate top tech talent and spur innovation by transforming their teams through strategic learning. More than 21,000 employees at elite companies worldwide have honed their digital fluency with our upskilling and reskilling initiatives. GA has also been recognized as one of Deloitte's Technology Fast 500, and Fast Company has dubbed us leaders in World-Changing Ideas as well as the #1 Most Innovative Company in Education.

GA is at the leading edge of creating practical solutions to one of the most pressing challenges of our time - the future of work. As recognized by The World Economic Forum, BCG, the OECD and more, these are big challenges to which only a few companies are offering real solutions. In this role, you'll be speaking every day to corporate leaders who rely on GA to help them apply these solutions to their workforce of the future.

Data Analytics Lead Instructor

In this immersive course, students learn and practice turning messy real-world datasets into actionable, data-driven insights they can communicate. We will be using Excel, SQL, Tableau, Power BI and Python as the primary tools for analysis. We are looking for an instructor to lead this In-Campus (based in Bahrain) Analytics course. This role is a full-time, temporary position that includes a start and end date for this cohort. There may be potential to receive an additional assignment offering, but additional assignments are not guaranteed.

This role is to be performed on-site, in-campus in Bahrain .

SKILLS AND QUALIFICATIONS

• You have strong experience using the following tools: Excel, SQL, Tableau, Power BI and Python.
• You are eager to shape the skills, minds, and trajectories of eager General Assembly students.
• You are the person that your colleagues naturally gravitate to when they are trying to figure something out.
• You have at least 5 years of work experience in a role where you've been responsible for cleaning messy data, analyzing the data and presenting your data based insights.

Preferred

• Experience working in-campus, in-person mentoring or in-person training etc.
• Backgrounds in adult learning, pedagogy and curriculum development
• Background in workshop facilitation and professional development
• Completion of a bachelor's degree or at least 10 years of applicable experience in lieu of a 4-year degree
• At least 2 years of practical experience within the last five years; 3 years preferred.
• Practical experience does not include teaching experience.
• Good moral character and strong decision making abilities
• Language, mathematical, reasoning, and computer skills that assure teaching effectiveness.

RESPONSIBILITIES AND DUTIES

• Teach and facilitate in class instruction based on the schedule proposed in the interview (full-time: Sunday through Thursday 9 AM to 5 PM; different scheduling for part-time)
• Work closely with your instructional team to provide students with meaningful and prompt feedback on their progress.
• Collaborate alongside GA staff in order to best meet the needs and learning styles of your students.
• Guide students through the development of real world projects that will showcase their abilities to hiring managers.
• Facilitate a dynamic and collaborative classroom community.
• Inspire students to persevere through the challenges of learning complex subjects.
• Contribute to the material and direction of an expanding global curriculum, ensuring the course remains cutting-edge and effective for students worldwide.

General Assembly will cover all travel-related expenses for qualified candidates.

Unless otherwise noted, remote positions can be performed from the following approved General Assembly operating countries.

United States of America (states of operation may vary), Canada (provinces of operation may vary), United Kingdom, Australia, and Singapore.

• Develop and refine AI and data science strategies for clients, aligning with their business objectives and market landscape.
• Lead the design and development of advanced analytical models and machine learning solutions.
• Identify new opportunities for data-driven innovation and AI application within client organizations.
• Manage data science projects from conceptualization to deployment, ensuring timely and successful delivery.
• Collaborate with clients to understand their data infrastructure, challenges, and opportunities.
• Mentor and guide junior data scientists and analysts, fostering a culture of excellence and continuous learning.
• Communicate complex analytical findings and strategic recommendations to C-level executives and stakeholders.
• Stay current with the latest advancements in AI, machine learning, statistical modeling, and data science techniques.
• Contribute to the development of the firm's data science and AI thought leadership.
• Drive business development efforts, including contributing to proposals and client pitches.

• Ph.D. or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• 10+ years of experience in data science, with a significant focus on AI strategy, machine learning, and analytics.
• Proven track record of leading successful AI and data science projects and teams.
• Deep understanding of various machine learning algorithms, statistical modeling techniques, and AI platforms.
• Expertise in programming languages such as Python or R, and proficiency with relevant libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
• Exceptional analytical, strategic thinking, and problem-solving skills.
• Outstanding communication, presentation, and stakeholder management skills.
• Experience in management consulting or advising clients on technology strategy is highly desirable.

• Lead the design and development of advanced machine learning models and statistical algorithms.
• Mentor and guide a team of data scientists, fostering a culture of learning and innovation.
• Collaborate with business units to identify opportunities for data-driven solutions.
• Perform complex data analysis, interpretation, and visualization to derive actionable insights.
• Develop and maintain data pipelines and ensure data quality and integrity.
• Communicate findings and recommendations to senior management and stakeholders.
• Stay abreast of the latest advancements in data science and artificial intelligence.
• Contribute to the overall data strategy and roadmap of the organization.

• Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, or a related field.
• 8+ years of progressive experience in data science and machine learning.
• Expertise in Python or R, including advanced statistical and ML libraries.
• Proficiency with SQL and experience with big data platforms (Spark, Hadoop).
• Strong understanding of data mining, predictive modeling, and statistical analysis.
• Demonstrated experience in leading data science projects and teams.
• Excellent problem-solving, critical thinking, and communication skills.
• Experience with data visualization tools (e.g., Tableau, Power BI) is a plus.

• Lead the design, development, and implementation of advanced machine learning models and analytical solutions.
• Mentor and guide a team of data scientists, fostering a culture of innovation and technical excellence.
• Identify business challenges and opportunities where data science can provide solutions.
• Extract, clean, and transform large, complex datasets from various sources.
• Perform rigorous statistical analysis and hypothesis testing.
• Develop and deploy predictive models for forecasting, classification, and clustering.
• Communicate complex analytical findings and recommendations clearly to stakeholders.
• Stay abreast of the latest advancements in data science, machine learning, and artificial intelligence.
• Collaborate with engineering and product teams to integrate data science models into production systems.

• Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of 7 years of experience in data science or machine learning, with a proven track record of leading projects and teams.
• Expertise in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and experimental design.
• Proficiency in Python or R, including relevant data science libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with big data technologies (e.g., Spark, Hadoop) and SQL.
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Excellent problem-solving, analytical, and communication skills.
• Ability to translate business needs into data science problems and vice-versa.

• Lead the design and implementation of advanced statistical models, machine learning algorithms, and data mining techniques to solve complex business problems.
• Oversee the end-to-end data science project lifecycle, from problem definition and data exploration to model development, validation, deployment, and monitoring.
• Mentor, coach, and develop a team of data scientists, fostering a collaborative and high-performing environment.
• Collaborate with stakeholders across various departments to identify key business challenges and opportunities where data science can provide significant value.
• Develop and implement data strategies, ensuring data quality, integrity, and accessibility for analytical purposes.
• Evaluate and recommend new technologies, tools, and methodologies to enhance the team's capabilities and efficiency.
• Communicate complex analytical findings and recommendations clearly and effectively to both technical and non-technical audiences through presentations and reports.
• Drive the adoption of data-driven decision-making processes throughout the organization.
• Stay abreast of the latest research and advancements in data science, machine learning, and artificial intelligence.
• Ensure ethical considerations and best practices are applied in all data science initiatives.

• Ph.D. or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Physics, or equivalent practical experience.
• Minimum of 6-8 years of progressive experience in data science, with a proven track record of leading impactful projects and teams.
• Expertise in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and data mining techniques.
• Proficiency in programming languages commonly used in data science, such as Python (with libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch) and R.
• Strong experience with SQL and database technologies, as well as big data platforms (e.g., Spark, Hadoop).
• Demonstrated ability to translate complex business problems into data science solutions.
• Excellent leadership, mentorship, and team management skills.
• Superb communication, presentation, and storytelling abilities.
• Experience working in a fully remote environment, demonstrating strong self-discipline and time management.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their data science services is a plus.

• Design, build, and maintain scalable data pipelines and ETL/ELT processes.
• Develop and manage robust data warehousing solutions.
• Ensure data quality, integrity, and reliability across all data systems.
• Lead and mentor a team of data engineers.
• Collaborate with data scientists and analysts to provide data support.
• Optimize data infrastructure for performance and cost-efficiency.
• Implement data governance and security best practices.
• Select and implement appropriate big data technologies.
• Automate data processes and improve operational efficiency.
• Contribute to the overall data strategy and roadmap.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• Minimum 7 years of experience in data engineering or a related role.
• Proven experience in designing and implementing data warehousing solutions.
• Proficiency in SQL and experience with various database systems (e.g., PostgreSQL, Snowflake, Redshift).
• Hands-on experience with big data technologies (e.g., Spark, Hadoop).
• Strong programming skills in Python, Scala, or Java.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services.
• Familiarity with data orchestration tools (e.g., Airflow, Prefect).
• Excellent leadership, communication, and problem-solving skills.
• Experience with data modeling and schema design.

• Lead the development and implementation of advanced analytical models and machine learning algorithms.
• Translate complex business challenges into data science problems and solutions.
• Mentor and guide a team of data scientists, fostering their professional growth.
• Collaborate with stakeholders across departments to understand their data needs and deliver actionable insights.
• Design and execute A/B tests and other experiments to validate hypotheses.
• Develop and maintain robust data pipelines and infrastructure.
• Stay abreast of the latest advancements in data science, machine learning, and AI.
• Communicate complex findings and recommendations clearly to both technical and non-technical audiences.
• Ensure the ethical and responsible use of data and AI.
• Contribute to the strategic direction of the company's data science capabilities.

• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
• Extensive experience in data science, machine learning, and statistical modeling.
• Proficiency in programming languages such as Python or R, and libraries like TensorFlow, PyTorch, scikit-learn.
• Strong SQL skills and experience with big data technologies (e.g., Spark, Hadoop).
• Proven experience in leading data science projects and teams.
• Excellent understanding of cloud platforms (AWS, Azure, GCP).
• Exceptional analytical, problem-solving, and critical thinking skills.
• Strong communication and interpersonal skills, with the ability to present complex information effectively.
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Familiarity with MLOps principles and practices.

• Lead the development and implementation of advanced analytical models and machine learning algorithms.
• Define key performance indicators and metrics to measure business impact.
• Extract, clean, and transform large, complex datasets from various sources.
• Conduct exploratory data analysis to identify trends, patterns, and insights.
• Develop predictive models for forecasting, classification, and clustering.
• Visualize data and communicate complex findings clearly to technical and non-technical audiences.
• Mentor and guide junior data scientists and analysts.
• Collaborate with engineering and product teams to deploy models into production environments.
• Stay current with the latest advancements in data science, machine learning, and AI.
• Drive data-driven decision-making across the organization.

• Ph.D. or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Minimum of 8 years of experience in data science or a related analytical role, with a proven track record of leading projects.
• Expertise in statistical modeling, machine learning algorithms, and predictive analytics.
• Proficiency in programming languages such as Python or R, and experience with data science libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with big data technologies (e.g., Spark, Hadoop) and database querying (SQL).
• Strong data visualization skills (e.g., Tableau, Power BI, Matplotlib).
• Excellent communication, leadership, and interpersonal skills.
• Ability to work independently and manage multiple projects effectively in a remote setting.