Role: Algorithms Developer

Level: Mid-Level

Location: Hybrid / Remote

Domain: Regulated Data & LLM-Enabled Decision Systems

Reports to: Head of Algorithms / AI Lead

About the Role

We are looking for a mid-level Algorithms Developer to join our algorithms and data team and contribute to the development of data-driven decision systems in a regulated environment.

The role focuses on designing and implementing algorithmic logic, data analysis, and ML-assisted decision pipelines, with exposure to LLM-enabled components as part of broader systems. The position involves working in an environment where requirements may be partially defined or evolve over time, requiring sound judgment, independence, and strong communication skills.

Responsibilities

· Design, implement, and maintain algorithmic components for data analysis, scoring, ranking, and decision support

· Contribute to systems that incorporate ML and LLM-based components alongside deterministic logic

· Analyze large datasets to identify trends, patterns, and actionable signals

· Implement and maintain ML-based models (e.g., classification, regression, ranking, clustering) under guidance

· Translate business logic, domain constraints, and regulatory requirements into robust, testable algorithms

· Contribute to end-to-end decision pipelines combining deterministic, probabilistic, and ML-based outputs

· Operate effectively under vague or evolving requirements by clarifying assumptions and proposing pragmatic solutions

· Monitor algorithm and model performance, data quality issues, edge cases, and potential drift

· Contribute to explainability, confidence estimation, and error analysis where applicable

· Communicate technical concepts, decisions, and trade-offs clearly to cross-disciplinary stakeholders

· Write clear documentation describing algorithms, assumptions, limitations, and expected behavior

· Participate in code reviews and uphold engineering best practices

Required Qualifications

· BSc (or higher) in Computer Science, Mathematics, Engineering, or a related field

· 2–5 years of experience in algorithmic development or applied ML roles

· Strong proficiency in Python and experience with data manipulation libraries (e.g., pandas, NumPy)

· Solid understanding of classical machine learning models and evaluation methodologies

· Experience working with large, structured or semi-structured datasets

· Strong analytical reasoning and problem-solving skills

· Ability to work independently while collaborating effectively within a team

· Clear written and verbal communication skills

Desired Qualities

· Ability to operate effectively in ambiguous problem spaces with incomplete or evolving requirements

· High level of ownership, initiative, and self-direction

· Strong communication skills with technical and non-technical stakeholders

· Comfort working across disciplines such as product, engineering, and domain experts

· Pragmatic mindset balancing correctness, risk, and delivery

Nice to Have

· Prior experience in healthcare, insurance, or other regulated industries

· Exposure to LLM-based systems or NLP workflows

· Familiarity with SQL and analytical databases

· Exposure to feature engineering, model monitoring, or explainability techniques

· Experience contributing to production ML systems

What Success Looks Like

· Independently implementing algorithmic features from high-level specifications

· Delivering reliable, maintainable, and well-documented code

· Demonstrating sound judgment in the face of ambiguity

· Proactively identifying risks, edge cases, and data issues

· Growing toward ownership of defined algorithmic components