Production Research Data Analyst

Bayer CropScience Limited; Lichtenburg; On-site; ZAR 450 000 - 600 000; Full time

Job summary

A leading agricultural technology company is seeking a Production Research Data Analyst to support data governance and analytics across Africa. The role involves building dashboards, conducting data analyses, and ensuring safety compliance. Ideal candidates should possess a BSc/MSc in a relevant field and expertise in programming languages such as R and Python. This position offers a chance to engage in impactful projects within a collaborative team environment.

Qualifications

• 2 years’ experience in a relevant Agricultural discipline.
• Hands-on experience with dashboard building and reporting.
• Strong record of problem-solving and innovation.

Responsibilities

• Build and validate dashboards using visualization software.
• Compile documentation of analytical processes.
• Perform statistical data analyses to answer research questions.

Skills

R programming

Python

SQL

Data analysis

Dashboard design

Statistical insight

Education

BSc or MSc in Computer Science, Data Science, Mathematics, Statistics, Biological Sciences, Computational Biology, Agriculture

Tools

Tableau

TIBCO Spotfire

Google Big Query

Job description

Production Research Data Analyst

Purpose:

• The Production Research Data Analyst role is responsible for supporting the success of delivering the pipeline and data insights.
• This role will support activities related to data governance, analysis and reporting to internal and external stakeholders across Africa.
• Furthermore, responsibilities include adherence to Bayer safety, quality, and operational procedures.

Scope:

• Regional

Key Responsibilities:

• Building and validating dashboards using preferred visualization software.
• Compiling documentation of analytical processes and results, adhering to agreed documentation standards.
• Supporting process data mining from IT systems and databases.
• Extract actionable insights from raw data.
• Performing quality control on collected Production Research data.
• Performing statistical data analyses to answer specific research questions.
• Providing analytics support to various projects locally.
• Providing support to stakeholders on data related deliverables using in-house analytics and reporting tools.

HSE Responsibilities:

• Leading HSE efforts according to ISO 45001 and Bayer safety standards focusing on legal compliance and identifying safety risks applying the HIRA methodology.
• Adherence to all applicable legislation, Bayer safety policies and procedures.
• Actively promoting the Bayer safety culture and best practices.
• Participation in compiling Risk assessments and Job safety analysis.
• Actively recording safety observation and near misses.
• Participating in 5WHY problem solving identifying corrective and preventative actions.

Key Working Relations:

• Data Insights and Pipeline Advancement Unit
• SSA and RSA Research and Testing Missions
• Agronomy and Technology Deploy Mission
• Foundation and Commercial Seed Production
• Production Management
• Production Quality
• Breeding (R&D)
• Portfolio Management

Qualifications & Experience

Education:

• BSc or MSc in Computer Science, Data Science, Mathematics, Statistics, Biological Sciences, Computational Biology, Agriculture or similar.
• 2‑years’ experience in a relevant Agricultural discipline (agricultural research, plant physiology, plant breeding or related field).

Experience:

• Hands‑on experience designing and building dashboards and reports using visualization tools.
• Proven track record of successfully reporting data insights to stakeholders.
• Strong record of problem‑solving and innovation.
• Experience working in a team‑based environment and capacity to influence within matrixed organizations (relationships and network).
• Data mining and wrangling experience using programming languages such as R.
• Proficient in downloading data from databases using software and tools such as Google Big Query.

Qualifications:

Required:

• Strong programming skills in R, Python, SQL.
• Strong aptitude for statistics.
• Experience with visualization software such as Tableau and TIBCO Spotfire.
• Proficiency in Machine Learning and Statistics algorithms and concepts (Mixed Models, Random Forest, Deep Learning, SVM, SAS JMP, etc.).
• Experience with data mining and statistical techniques (Logistic Regression, Linear Regression, Decision Trees, etc.).
• Problem solving ability and experience in analyzing and presenting complex data.
• Organizational, interpersonal, and written communication skills.

Desired:

• A track record of successful project delivery with analytical interpretation skills.
• Willingness to be flexible and work in diverse fields and corporate conditions.
• Sound decision making and judgement skills.
• Detail and results oriented with the ability to work independently.
• Willingness to extend personal data science and statistical interests to agriculture and/or experience working with agricultural/biological scientific data.

Functional Competence:

• Ability to work in a fast‑paced global and multi‑cultural seed company.
• Challenging the status quo to improve processes and the way things are done.
• Organizational, interpersonal, and written communication skills.
• Excellent data interpretation skills.
• Detail and results oriented with the ability to work independently.

Application Period: 6 - 20 November 2025

Reference Code: 856176

Division: Crop Science

Location: South Africa : North West : Lichtenburg

Functional Area: Information Technology

Position Grade: E13

Employment Type: Regular

Work Time: Standard

Address: 9 Country Estate Drive, Waterfall City, Johannesburg, 2090.
P O Box 143
Isando, 1600, South Africa

Telephone: N/A

E‑Mail: [e-mail]

Bayer welcomes applications from all individuals, regardless of race, national origin, gender, age, physical characteristics, social origin, disability, union membership, religion, family status, pregnancy, sexual orientation, gender identity, gender expression or any unlawful criterion under applicable law. We are committed to treating all applicants fairly and avoiding discrimination.