Industry Artificial Intelligence (AI) & Analytics
Work Experience 8+ years
Remote Job
About Us
OmniReach delivers digital excellence worldwide, driving Digital Transformation and Commerce Enablement through Cloud, Microservices, AI, Data Science and Security.
You'll work on meaningful global projects across North America, Europe, Asia, and Australia, blending global scale with local insight.
Job Description
This is a remote position.
We are seeking a Senior Data Scientist to design, build, and deliver world-class AI/ML models that solve critical business challenges. You will work on complex data sets, apply advanced mathematical and statistical techniques, and deploy AI models that drive measurable impact. This role demands deep expertise in mathematical modelling, machine learning, and real-world problem-solving.
Key Responsibilities
Translate complex business objectives into mathematical formulations, predictive models, or optimization solutions.
Conduct exploratory data analysis (EDA), feature selection, and feature engineering using advanced statistical techniques.
Build, train, tune, and evaluate machine learning and deep learning models for various use cases: NLP, computer vision, forecasting, recommendations.
Research, prototype, and experiment with state-of-the-art models (e.g., Transformers, LLMs, Graph Neural Networks) and adapt them to client projects.
Perform model interpretability (SHAP, LIME, Explainable AI) and communicate model outputs to non-technical stakeholders.
Implement statistical testing (A/B testing, hypothesis testing) to validate model impact in production settings.
Deploy models using APIs or lightweight serving platforms and collaborate with engineering teams for MLOps.
Stay current with academic and industry research to integrate new techniques and algorithms.
Requirements
Required Skills
8+ years in Data Science, Machine Learning, or Applied Mathematics roles.
Strong academic foundation: Statistics, Probability Theory, Linear Algebra, Optimization, Calculus.
Expertise in Python (pandas, NumPy, scikit-learn, TensorFlow, PyTorch, HuggingFace).
Hands-on experience building production-grade models and measuring business impact.
Strong background in ML Evaluation (ROC-AUC, F1, Precision-Recall, Cost-sensitive metrics).
Familiarity with cloud ML services (SageMaker, Vertex AI, Azure ML).
Knowledge of model fairness, bias detection, and responsible AI practices.
Preferred Skills
Experience working with LLMs, NLP, Computer Vision, or Time-Series Forecasting at scale.
Publications in peer-reviewed conferences or applied research experience.
Familiarity with AutoML, Reinforcement Learning, Bayesian Optimization.
Highly analytical and loves working with messy, ambiguous, real-world datasets.
Has strong scientific rigor and business intuition to frame modelling decisions.
Passionate about building models that are interpretable, scalable, and impactful
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