Jobs
Required Skills
Python
SQL
VBA
Excel
Power BI
Data analysis
Statistical analysis
Job Purpose and Impact
The Data & Analytics Consultant is responsible for collecting, processing, and analyzing complex datasets and builds detailed reports and dashboards using specific data tools to generate actionable insights. This job is critical for the effective provisioning of data, analytics, models, solutions, findings and presentation of insights to business stakeholders to meet business objectives across Asia Pacific.
- Key Accountabilities
- DATA COLLECTION & ANALYSIS: Gathers, processes, prepares, and analyzes moderately complex datasets to extract significant insights, develop and maintain automated reporting systems to streamline data analysis.
- DATA / STATISTICAL ANALYSIS: Conducts moderately complex data analysis to uncover trends, patterns, and actionable insights for decision-making. Supports statistical analysis execution to identify trends, patterns, and anomalies in data using statistical software and programming languages for data manipulation and analysis.
- REPORTING & VISUALIZATION: Implements detailed reports and dashboards using various tools, designs and completes data visualizations to communicate moderately complex data clearly.
- ANALYTICS, AI / ML AND DATA SCIENCE: Application of analytics and data science-driven techniques, and hands-on delivery of AI/ML-driven analytical models and solutions
- PROCESS IMPROVEMENT: Implements found opportunities to improve data collection and reporting processes, deliver automation solutions and applies standard methodologies for data management and reporting.
- COLLABORATION: Works closely with multi-functional teams to support data needs, identifies value-creation opportunities, solves data problems and delivers solutions in partnership with business stakeholders, project working teams, digital technology and data engineering teams.
- QUALITY ASSURANCE & DATA VALIDATION: Performs moderately complex analysis in support of the completeness, consistency, accuracy, and security of data. Understands and monitors the transaction and master data lifecycle, and proactively manages data quality.
Qualifications:
- Bachelor's degree in a related field (e.g. Data Science, Statistics, Computer Science, Business Analytics) or equivalent experience.
- Minimum of four years of relevant work experience.
- Confirmed skills of analyzing data content for reporting or analytics solutions.
- Proficiency in data manipulation / programming languages such as Python, SQL, VBA, and applications such as MS Excel and Power BI to analyze, model, visualize and communicate data insights.
- Strong understanding of data warehousing, data lakes, cloud data platforms (e.g. AWS, Snowflake) and related big data technologies.
- Able to automate data (transformation) workflows and build low-code applications leveraging the Power Platform (Power Automate, Power Apps, Power Query).
- Familiarity with (predictive) analytics, AI/ML and data science.
- Solid business understanding and financial acumen to draw accurate insights and use information as a strategic value-creation tool.
- Excellent communication and stakeholder management skills.
- Comfortable with agile workflow management and able to manage multiple priorities simultaneously.
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About Cargill

Cargill
PublicMultinational food company.
10,001+
Employees
Minnetonka
Headquarters
Reviews
3.7
9 reviews
Work Life Balance
2.8
Compensation
4.0
Culture
3.2
Career
4.1
Management
3.0
65%
Recommend to a Friend
Pros
Good learning opportunities and exposure to different areas
Competitive pay and benefits
Supportive teams and bosses
Cons
Heavy workload and time-sensitive demands
Management favoritism and lack of appreciation
High turnover rate
Salary Ranges
477 data points
Junior/L3
L2
L3
L4
L5
L6
Mid/L4
Senior/L5
Intern
Director
Junior/L3 · Production
95 reports
$42,472
total / year
Base
$42,472
Stock
-
Bonus
-
$27,969
$64,496
Interview Experience
5 interviews
Difficulty
2.6
/ 5
Duration
14-28 weeks
Offer Rate
20%
Experience
Positive 80%
Neutral 20%
Negative 0%
Interview Process
1
Application Review
2
HR Screen
3
Technical Interview with Manager
4
Panel Interview
5
Plant Tour/Site Visit
6
Offer
Common Questions
Behavioral/STAR
Technical Knowledge
Past Experience
Culture Fit
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