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ADI Global Distribution

Security product distribution

Data Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeNo salary listedHybrid

About the Job

Requirements

  • At least 3 years of hands-on experience in applied data science and machine learning, ideally in B2B, retail, or digital commerce environments.
  • Strong proficiency in Python, including experience with data science and machine learning libraries such as Pandas, NumPy, Scikit-learn, and visualization tools.
  • Advanced SQL skills, including the ability to write complex queries, procedures, and analytical transformations.
  • A solid understanding of classical machine learning algorithms and their real-world business applications.
  • Professional working proficiency in English for global collaboration and technical communication.

Responsibilities

  • Design, develop, and deploy predictive and prescriptive models to support customer experience optimization, demand forecasting, operations efficiency, and customer behavior analysis.
  • Apply machine learning and artificial intelligence techniques, including Gradient Boosting, Random Forests, support vector machines, LSTM, Transformers, and emerging artificial intelligence approaches, to solve business problems.
  • Build, maintain, and optimize customer-facing and internal analytical models, including recommendation systems, churn prediction, propensity modeling, customer segmentation, demand forecasting, matching, and assortment optimization.
  • Perform feature engineering, clustering, statistical modeling, and time-series analysis using structured and unstructured data sources.
  • Transition models from exploratory research environments, such as notebooks, into production-ready artifacts, including APIs, serialized models, and containerized solutions.
  • Collaborate with engineering teams to integrate end-to-end MLOps, including CI/CD pipelines, model versioning, automated deployment, monitoring, and retraining strategies.
  • Conduct advanced statistical analysis to identify trends, anomalies, and opportunities, and deliver actionable insights through reports and analytical outputs.
  • Support experimentation through A/B testing, KPI definition, causal inference, and measurement of business impact.
  • Partner with product, engineering, analytics, and business stakeholders to identify and prioritize data science opportunities aligned with organizational goals.
  • Communicate findings, including assumptions, limitations, trade-offs, and recommendations, to technical and non-technical audiences.
  • Share knowledge, promote best practices, mentor peers, and advocate for responsible and ethical use of artificial intelligence.

Desired Qualifications

  • Experience applying deep learning techniques, including sequence models such as LSTM and Transformer-based architectures.
  • Hands-on experience leveraging large language models for text classification, search, summarization, enrichment, or automation.
  • Practical experience designing or improving recommendation systems and personalization models.
  • Familiarity with MLOps best practices, including CI/CD pipelines, automated testing, deployment, monitoring, and retraining.
  • Experience with Snowflake or similar cloud-based data warehouse platforms.
  • Exposure to data engineering concepts, such as data pipelines, dbt, workflow orchestration, or streaming architectures.
  • Experience working with Azure cloud services and machine learning/artificial intelligence platforms.
  • Proficiency with GitHub for version control and collaborative development workflows.
  • Experience working in Agile/Scrum environments.

About the Company

ADI Global Distribution

Security product distribution

ADI Global Distribution supplies security, audiovisual, networking, fire, access-control and other low-voltage products to professional dealers and installers. Its catalog brings together equipment from many manufacturers, supported by branches, e-commerce, logistics and technical product expertise. Integrators and contractors use ADI to source components for residential, commercial and industrial systems. The company operates as a business-to-business distributor rather than a consumer electronics retailer or the manufacturer of a single technology brand. Its workforce brings together technical specialists, client delivery teams and business operations.

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Total funding
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