[CMI] Data Scientist

Software Mind

18h•Remote

About The Position

Software Mind develops solutions that make an impact for companies around the globe. Tech giants & unicorns, transformative projects, emerging technologies and limitless opportunities – these are a few words that describe an average day for us. Building cross-functional engineering teams that take ownership and crave more means we’re always on the lookout for talented people who bring passion and creativity to every project. Our culture embraces openness, acts with respect, shows grit & guts and combines employment with enjoyment. We are looking for a talented Data Scientist to join our team and work on innovative projects for our clients. Our mission is to help organizations unlock the full potential. You will own the creation of decision‑grade intelligence products by applying advanced analytics and statistics to transform complex multi‑source data into trusted, monetizable customer offerings.

Requirements

7 - 8+ years' experience in applied data science roles
Strong proficiency in Python, SQL, and ML libraries
Ability to translate data into presentable stories.
Experience delivering customer‑facing, revenue‑generating data products
Bachelor’s degree in computer science, Engineering, Information Systems, or related field

Responsibilities

Design, build, validate, and maintain predictive and prescriptive models across travel, risk, and location domains
Apply statistical methods, machine learning, and experimentation to improve data accuracy, completeness, and trust
Develop domain‑specific metrics, benchmarks, and risk scoring frameworks
Translate customer problems and market needs into analytical solutions and data products
Partner with Product Managers to define value propositions, pricing inputs, and success metrics
Contribute to roadmap prioritisation based on impact, feasibility, and monetisation potential
Define data quality rules, validation logic, and anomaly detection mechanisms
Ensure alignment with privacy, consent, and ethical AI standards in regulated environments
Support lineage, explainability, and auditability of analytical outputs
Work closely with Data Engineers to ensure model‑ready, reliable data pipelines
Collaborate with Machine Learning Engineers to operationalise models at scale
Communicate insights and recommendations clearly to technical and non‑technical stakeholders