Lead Data Scientist

At AbsenceSoft, we’re transforming the employee experience. Our secure, intuitive technology helps employers bring humanity, certainty, and efficiency to some of the most complex moments in the workplace. Built by HR professionals for HR professionals, we’re proud of where we’ve been and even more excited about where we’re going.

We’re seeking a Lead Data Scientist who will translate business challenges into intelligent models that scale. You will lead the design, development, and deployment of AI/ML models across a diverse range of applications—including predictive analytics, classification, semantic search, multi-modal processing (text, image, audio), and advanced LLM engineering. This role bridges domain understanding with deep technical modeling expertise, working closely with data engineers, AI software engineers, and product leaders.

What you'll do

• Lead the end-to-end lifecycle of ML models: scoping, data preparation, training, validation, deployment, and monitoring.
• Design traditional supervised and unsupervised learning models as well as deep learning models for NLP, vision, and audio tasks.
• Build, fine-tune, and evaluate large language models (LLMs), including MOE (Mixture of Experts), SLMs (Small Language Models), and other foundational architectures.
• Engineer LLMs using transformer-based architectures, with expertise in tokenization, embedding layers, encoders, multi-head attention, and positional encoding.
• Apply advanced techniques such as reinforcement learning with human feedback (RLHF), deep Q-learning, and parameter-efficient fine-tuning (PEFT).
• Collaborate with software engineers and AI product managers to operationalize models in scalable, production-grade environments.
• Conduct exploratory data analysis and experimentation to uncover insights that drive product and business decisions.
• Own the model evaluation framework and define metrics for performance, fairness, explainability, and robustness.
• Apply Responsible AI principles to ensure models are ethically developed and comply with global regulations (e.g., GDPR, HIPAA, AI Act).
• Partner with stakeholders to build AI features that serve compliance, leave, accommodations, and workforce intelligence domains.
• Lead the scientific and strategic direction for the modeling roadmap and mentor junior data scientists as the team scales.

What you'll bring

• 7+ years of experience in data science, with a proven track record delivering enterprise-grade ML models.
• Extensive experience with transformer architectures and building LLMs from the ground up.
• Proficiency in tokenizers, embedding techniques, self-attention mechanisms, encoder-decoder models, and multi-head attention.
• Hands-on experience with reinforcement learning, deep Q-learning, RLHF, and PEFT approaches.
• Expertise in Python and ML/DS libraries (pandas, NumPy, scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch).
• Experience developing models for NLP, computer vision, and/or audio using deep learning frameworks.
• Strong understanding of statistical modeling, experimental design, and model interpretability techniques.
• Experience collaborating with MLOps engineers to productionize models, monitor drift, and manage model lifecycle.
• Hands-on experience with large-scale data environments, feature engineering, and pipeline tooling (e.g., dbt, Airflow, Snowflake).
• Excellent communication skills with the ability to convey technical findings to non-technical stakeholders.
• Working knowledge of global AI and data regulations and how they affect model development and deployment.

Why join us

At AbsenceSoft, we LEAD with our values:

Lead with Innovation - We create meaningful change through intelligence, focus and passion.  We embrace curiosity, data, and insight to shape the future of our industry. Always innovating, learning and evolving.

Elevate Every Voice - Every perspective matters. We listen, learn, and build a culture where diversity of thought and experience drives better solutions and smarter decisions.

Achieve Together - The customer fuels everything we do. We share knowledge, collaborate, celebrate wins, and face challenges