Data Scientist Applied ML & AI

About the role

We are looking for a Data Scientist who can turn ambiguous business problems into measurable outcomes. Youll work across classical ML, statistics, forecasting, NLP, and LLMs, choosing the simplest approach that works—and proving it with data.

We don’t consider a model complete when it is trained. We care about whether it is used, deployed, and improves a meaningful metric.

What you’ll do

• Translate business questions into measurable objectives, target variables, and success metrics.
• Explore, clean, and join data using Python and SQL; identify data-quality issues, leakage, and bias.
• Build and evaluate classification, regression, forecasting, clustering, and recommendation models.
• Apply NLP and LLM techniques such as prompting, RAG, embeddings, and fine-tuning when they add measurable value.
• Establish baselines, conduct error analysis, and evaluate models using appropriate validation methods.
• Apply statistics, experimentation, and uncertainty analysis to support sound decisions.
• Work with engineering teams to deploy, monitor, and maintain models in production.
• Communicate findings, assumptions, trade-offs, and limitations to non-technical stakeholders.

Tech stack

Python • SQL • pandas • NumPy • scikit-learn • XGBoost / LightGBM • PyTorch • Hugging Face • Git • MLflow / W&B • AWS / Azure / GCP

You’ll fit if

• You have 4+ years of hands-on Data Science / Applied ML experience.
• You have shipped a model or analytical solution that people actually use.
• You can explain the baseline, evaluation metric, and business impact of your work.
• You have strong statistics and problem-solving fundamentals, beyond familiarity with libraries.
• You’re comfortable working across classical ML and modern AI, and can explain when a simpler solution is better.
• You communicate clearly and can work independently with business and engineering teams.