Data Scientist, Mid-Level

This is a fully remote position, open to applicants in Argentina.

📋 Description

• Lead the development of analytical, statistical, machine learning, and applied AI solutions for various business and client applications.

• Convert business inquiries into analytical methodologies, modeling strategies, hypotheses, features, evaluation techniques, and quantifiable outcomes.

• Create and implement segmentation, forecasting, propensity modeling, anomaly detection, experimental analysis, recommendation-focused studies, and decision-support tasks.

• Independently analyze structured, semi-structured, and select unstructured datasets.

• Construct, enhance, and sustain notebook-based workflows and reproducible analytical resources in Databricks and cloud platforms.

• Utilize machine learning and AI for classification, scoring, summarization, pattern recognition, feature generation, and enhancing business processes.

• Assess and implement LLM-enabled or AI-assisted workflows.

• Engage in model training, tuning, validation, performance assessment, and comparative analysis.

• Record assumptions, methodologies, feature logic, model choices, evaluation criteria, limitations, and findings.

• Collaborate with Data Analysts, AI Scientists, AI Engineers, Analytics Engineers, Data Engineers, and Architects.

• Enhance the reproducibility, evaluation standards, documentation, and scalability of analytical processes.

• Adhere to governance, privacy, and ethical data and AI standards.

• Participate in discussions with clients, articulating methods, findings, limitations, and implications in business terms.

• Employ approved AI-assisted workflows while ensuring human accountability for validation, interpretation, and recommendations.

⛳️ Requirements

• Minimum of 3 years of experience.

• Proficient understanding of statistics, probability, machine learning, and analytical problem-solving techniques.

• Capability to oversee recurring data science workstreams independently and produce reliable outcomes with minimal supervision.

• Strong grasp of supervised and unsupervised learning, feature engineering, model evaluation, error analysis, and framing analytical problems.

• Experience working with structured, semi-structured, and selected unstructured datasets.

• Knowledge of experimental design, model validation, and the interpretation of analytical and predictive outputs in business situations.

• Familiarity with applied AI techniques, including LLM-enabled workflows, text-oriented analysis, and AI-assisted feature extraction or classification.

• Experience with notebook-based development and collaborative data science workflows, particularly with Databricks.

• Excellent written and verbal communication skills in English.

• Ability to collaborate with distributed teams across the Americas and navigate various functions, time zones, and client contexts.

• Proficiency in Python, Jupyter Notebooks, Pandas, NumPy, scikit-learn, SciPy, Statsmodels, XGBoost, and LightGBM.

• Experience with Databricks, Apache Spark, PySpark, and MLflow.

• Knowledge of SQL, BigQuery, Snowflake, and cloud data platforms.

• Familiarity with Google Cloud Platform, Vertex AI, Microsoft Azure, Azure AI services, and Azure Machine Learning.

• Experience with OpenAI-compatible APIs or enterprise LLM platforms; prompt evaluation; embeddings; text analysis; and unstructured data processing.

• Proficiency in Matplotlib, Seaborn, Plotly, Looker, Power BI, and Tableau.

• Experience with Git, GitHub, and Azure DevOps.

🏝️ Benefits

• Flexibility with options for remote and hybrid work (dependent on country).

• Opportunities for career advancement, including international mobility and professional development programs.

• Access to learning and development resources, including cutting-edge tools, training, and industry experts.

• Comprehensive medical, dental, and vision insurance for you and your family.

• Employer contributions to Health Savings Accounts.

• An inclusive culture with accessibility accommodations during the interview process.