Data Scientist

Turn Data Into Impact — Start Your Analytics Career With Purpose
Are you curious about how data can shape billion-dollar decisions? Do you enjoy solving complex problems, exploring patterns, and developing innovative tools? If you're ready to grow your skills in a collaborative and intellectually driven environment, this is your opportunity to contribute to real-world change from day one.
We’re seeking a junior-level Data Scientist who’s excited to learn, innovate, and apply machine learning to real-world challenges in capital project analysis. You'll work on projects that impact industries like energy, infrastructure, pharma, and consumer products — all while collaborating with a team of data-minded professionals who value creativity, rigor, and a strong analytical mindset.

Responsibilities

• Develop and deploy machine learning models to support predictive analytics and data-driven decision-making.
• Research and test new algorithms to improve model performance and efficiency.
• Build tools and applications using large language models (LLMs) for internal use and client engagement.
• Prepare, analyze, and present insights using structured and unstructured data.
• Collaborate with cross-functional teams and contribute to new product development.
• Work with stakeholders (technical and non-technical) to translate complex data into actionable recommendations.
• Contribute to the enhancement of benchmarking and analytics tools across multiple sectors.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• 1–3 years of hands-on experience in data science or machine learning, through academic, research, or industry projects.
• Proficiency in Python and/or R, with working knowledge of SQL.
• Familiarity with machine learning libraries such as scikit-learn, PyTorch, or similar.
• Exposure to Large Language Models (LLMs) and experience implementing them in real-world workflows (e.g., RAG, agentic tools).
• Basic understanding of MLOps principles and version control tools like Git.
• Experience using cloud platforms (AWS, Azure) is a plus but not required.
• Strong communication skills — able to explain technical ideas to non-technical stakeholders.
• A project portfolio, GitHub profile, or sample work that showcases your technical skills and creativity.

Build the Future, One Dataset at a Time
If you're ready to kick-start your data science career in a role that blends technical depth, real-world impact, and professional growth, we want to hear from you. You'll be part of a mission-driven team that values analytical thinking, innovation, and lifelong learning — and you’ll help shape smarter decisions across major global industries.
Apply today with your resume, cover letter, portfolio (GitHub or similar), and salary expectations. Let’s turn your passion for data into real-world value.