Data Scientist

🕒 March 26

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Lingaro

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2008

🤖 Artificial Intelligence

🤝 B2B

🏢 Enterprise

Artificial Intelligence • B2B • Enterprise

Lingaro is an end-to-end data services and analytics partner for global brands and enterprises, delivering data strategy, platform engineering, AI/ML (including generative AI), and data governance to unlock business value. It combines domain-focused analytics (supply chain, commercial/RGM, digital commerce, sustainability) with data platforms, visualization, MLOps, and secure cloud (Google Cloud) integrations, plus a creative arm (ALCHEMY) for data-driven brand and commerce experience design.

📋 Description

• Work on end‑to‑end classification and forecasting use cases, including problem framing, data preparation, model development, evaluation, and basic deployment support (e.g., demand forecasting, churn prediction). • Explore and clean data; perform Exploratory Data Analysis (EDA) to understand datasets and identify data quality issues. • Engineer features for tabular and time‑series data. • Train, validate, and tune standard Machine Learning models (e.g., logistic regression, decision trees, ensemble methods, gradient boosting, classical time‑series models, simple neural networks). • Evaluate models using appropriate metrics with clear impact on business KPIs. • Build clear visualizations and deliver concise reports to present insights and model results to business stakeholders. • Collaborate with data engineers and AI engineers to bring models to production (batch scoring, APIs, monitoring, dashboards). • Document data sources, modeling assumptions, and experiment results in a reproducible manner (notebooks, reports, wikis). • Translate business needs into technical goals by defining success metrics, auditing data feasibility, and aligning with stakeholder expectations. • Participate in pre‑sales activities (for senior consultant level).

🎯 Requirements

• Commercial experience with various classical data science and ML models (e.g., decision trees, ensemble models, linear/logistic regression). • Strong knowledge of customer analytics concepts or advanced forecasting techniques. Experience in: • Hyperparameter tuning • Model validation frameworks • Requirements gathering and translating business needs into technical plans • Feature engineering and model evaluation • Previous experience in an analytical role supporting business functions (a plus). • Fluency in Python and working knowledge of SQL. • Knowledge of common DS/ML libraries. • Solid experience with at least one cloud platform: Databricks, GCP, or Azure. • Basic computer programming skills and understanding of core programming concepts. • Strong business acumen. • Experience with advanced modeling techniques such as deep learning or reinforcement learning (a plus). • Ability to develop creative solutions to customer challenges. • Nice to have: • Understanding of causal machine learning. • Experience working with big data and distributed computing environments. • Proven commercial experience with successful forecasting projects. • Experience with Object-Oriented Programming (OOP) in Python. • Experience with MLOps practices and tooling.Familiarity with additional languages such as R or Scala.