Data Scientists

**Job Summary**:
**Salary**
S$6,500 - S$8,500 / Monthly

**Job Type**

**Seniority**

Junior

**Years of Experience**
At least 1 year

**Tech Stacks**
DynamoDB play Analytics R Flow NoSQL PostgreSQL Python

At Tetrixx, when it comes to improving the environment and building sustainable solutions, no challenge is too big to take on. Tetrixx is where your years of intense training and experience come to make sense, giving you real purpose, immense pride in what you do and, more importantly, clarity on why you do it.

We are an innovative technology startup, swimming intently in the Logistics and Supply Chain waters. Our mission is to revolutionize the way businesses manage their logistics operations through cutting-edge technology solutions. We are seeking an experienced **Data Scientist & Analyst** to join our dynamic team and play a crucial role in shaping the future of Logistics. So, if you are passionate about being an instrumental part of our journey and delivering world class end-to-end solutions that engage our clients, generate tangible value for them and help making their respective industries a little bit smarter and waste free, then stop what you are doing and get in touch. We would love to hear from you

**Job Summary**:
As an experienced **Data Scientist & Analyst** with a solid track record of engaging with Data Products, you will be collaborating closely with various stakeholders, including Product Managers, Sales & Business teams, Clients, and Tech teams.

With the right background and attitude, you will be able to play a critical role in shaping our data-driven initiatives and driving value generation from highly complex and large datasets for our clients.

**Responsibilities**:

- Stakeholder Collaboration: Collaborate with cross-functional teams to understand business requirements and translate them into data analysis objectives.
- Stakeholder Collaboration: Work with Data Engineers to help develop and maintain automated data pipelines to ensure a continuous flow of accurate and timely data.
- Stakeholder Collaboration: Collaborate with Data Engineers, Data Scientists, and Infrastructure experts to optimize Data Architecture for improved performance and scalability.
- Data Product Development: Design, develop, and implement robust Data Models for efficient Data Processing in a cloud-based environment.
- Data Product Development: Conduct exploratory data analysis to identify trends, patterns, and anomalies in large datasets.
- Data Product Development: Perform in-depth data validation and quality assurance to guarantee the reliability of analytical results.
- Data Product Development: Create visually compelling and insightful reports and dashboards for key stakeholders.
- Efficiency Improvement: Use your expertise in Statistical Analysis, Machine Learning, and Predictive and Adaptive Analytics to enhance data-driven decision support for our clients.
- Self-Improvement: Stay abreast of industry trends and emerging technologies to propose and implement innovative solutions.
- Communication: Effectively communicate complex data findings and insights to diverse stakeholders, translating technical concepts into actionable insights.
- Independence: Demonstrate a high degree of independence in problem-solving, project management, and decision-making.
- Efficiency Improvement: Identify process bottlenecks and propose strategies to enhance efficiency and effectiveness in Data Analysis and product development.

**Preferred Qualifications**:

- Bachelor's degree in Computer Science, Electronic Engineering, or a related field (Master's preferred).
- 7- 10 years of hands-on experience in Data Analysis and/or Data Product Development.
- Strong proficiency in Data Analysis tools and programming languages (e.g., Python, R, SQL).
- Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment.
- Excellent communication and teamwork skills with the ability to convey complex technical concepts to non-technical stakeholders.
- Solid experience of working in Agile/Scrum development environments.
- Proficiency in relational databases (e.g., Postgres) and NoSQL databases (e.g., DynamoDB) is a plus.