Data Science Lead – MLOps, Advanced Analytics

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Resilient Co.

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2020

💼 Consulting

📣 Marketing

👥 HR Tech

Consulting • Marketing • HR Tech

Resilient Co. is a technology consulting and recruiting firm focused on supporting the growth of startups and organizations within the IT market. With a diverse and experienced team, the company offers a range of services including talent acquisition, coaching, and training tailored to the needs of tech clients. Operating with a 'Remote First' culture, Resilient Co. emphasizes collaboration and adaptability to navigate the challenges of the technology recruitment landscape, positioning itself as a strategic partner for businesses looking to build strong tech teams.

📋 Description

• Architect and deliver end-to-end production-grade ML and AI systems using MLOps principles • Oversee the full lifecycle from hypothesis and exploratory data analysis through feature engineering, model selection, and production deployment • Bridge Data Engineers and business stakeholders by translating KPIs into objective functions • Architect automated pipelines for data validation, model profiling, and hyperparameter tuning using Azure Machine Learning Services • Establish monitoring for data drift and concept drift after deployment • Steer development of predictive models within CI/CD/CT frameworks • Transform large raw datasets into scalable enterprise intelligence using Azure Databricks, Spark, and Azure ML

🎯 Requirements

• 5–8 years of total experience • 4+ years of hands-on Data Science experience • 2+ years leading technical teams or complex projects • BE/BS or MS/PhD in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field • Proficiency in supervised and unsupervised learning, Gradient Boosted Trees, XGBoost, LightGBM, Random Forests, and Neural Networks • Mastery of hypothesis testing, Bayesian inference, and error analysis • Ability to design complex experiments and A/B tests • Knowledge of loss-function customization and optimization algorithms including Gradient Descent and Genetic Algorithms • Advanced proficiency in Python, Pandas, Scikit-learn, PySpark/TensorFlow, and SQL • Hands-on experience with PySpark and Databricks for distributed processing of petabyte-scale datasets • Expert-level knowledge of MLFlow and Kubeflow or Azure Pipelines • Experience with Docker/Kubernetes and deploying batch inference jobs • Advanced forecasting experience with Prophet, ARIMA, or LSTM networks is highly desirable • Technical mentorship, Agile/Scrum familiarity, and stakeholder-management abilities are listed as nice to have

🏖️ Benefits

• 3-month initial contract with rolling/ongoing project and quarterly renewals based on performance • BYOD (Bring Your Own Device) • No overtime required