Data Scientist, Mid-Level

🔥 0 minutes ago

🇦🇷 Argentina – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Valtech

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1997

💼 Consulting

📣 Marketing

☁️ SaaS

Consulting • Marketing • SaaS

Valtech is a global digital agency focusing on experience innovation. They strive to transform businesses through a combination of technology, marketing, and data strategies. Valtech helps companies elevate their digital presence and drive commerce strategies, enhance enterprise digital transformations, and unlock marketing and performance potential. They also utilize data and AI to help organizations harness the power of information. With offices around the world, Valtech partners with businesses to shape their digital futures, offering a range of services and insights designed to enhance customer experiences.

📋 Description

• Lead analytical, statistical, machine learning, and applied AI solutions for business and client use cases • Translate business questions into analytical approaches, modeling strategies, hypotheses, features, evaluation methods, and measurable outputs • Design and execute segmentation, forecasting, propensity modeling, anomaly detection, experimentation, recommendation-oriented analysis, and decision-support work • Analyze structured, semi-structured, and selected unstructured datasets independently • Build, refine, and maintain notebook-based workflows and reproducible analytical assets in Databricks and cloud environments • Apply machine learning and AI to classification, scoring, summarization, pattern detection, feature generation, and business process improvement • Evaluate and apply LLM-enabled or AI-assisted workflows • Participate in model training, tuning, validation, performance review, and comparative evaluation • Document assumptions, methodology, feature logic, model decisions, evaluation criteria, limitations, and findings • Partner with Data Analysts, AI Scientists, AI Engineers, Analytics Engineers, Data Engineers, and Architects • Improve reproducibility, evaluation practices, documentation, and scalability of analytical workflows • Follow governance, privacy, and responsible data and AI standards • Participate in client-facing discussions and explain methods, findings, limitations, and implications in business language • Use approved AI-assisted workflows while maintaining human accountability for validation, interpretation, and recommendations

🎯 Requirements

• 3+ years of experience • Strong working knowledge of statistics, probability, machine learning, and analytical problem solving • Ability to independently manage recurring data science workstreams and deliver reliable outputs with minimal oversight • Strong understanding of supervised and unsupervised learning, feature engineering, model evaluation, error analysis, and analytical problem framing • Ability to work with structured, semi-structured, and selected unstructured datasets • Working knowledge of experimentation design, model validation, and interpretation of analytical and predictive outputs in business contexts • Familiarity with applied AI methods, including LLM-enabled workflows, text-oriented analysis, and AI-assisted feature extraction or classification • Familiarity with notebook-based development and collaborative data science workflows, including Databricks • Strong written and verbal communication skills in English • Ability to collaborate across distributed teams in the Americas and across functions, time zones, and client contexts • Python, Jupyter Notebooks, Pandas, NumPy, scikit-learn, SciPy, Statsmodels, XGBoost, and LightGBM • Databricks, Apache Spark, PySpark, and MLflow • SQL, BigQuery, Snowflake, and cloud data platforms • Google Cloud Platform, Vertex AI, Microsoft Azure, Azure AI services, and Azure Machine Learning • OpenAI-compatible APIs or enterprise LLM platforms; prompt evaluation; embeddings; text analysis; unstructured data processing • Matplotlib, Seaborn, Plotly, Looker, Power BI, and Tableau • Git, GitHub, and Azure DevOps

🏖️ Benefits

• Flexibility, with remote and hybrid work options (country-dependent) • Career advancement, with international mobility and professional development programs • Learning and development, with access to cutting-edge tools, training and industry experts • Medical, dental, and vision insurance for you and your family • Employer contributions to Health Savings Accounts • Inclusive culture and accessibility accommodations during the interview process