Company Overview At Insight Fusion Analytics, we specialize in data analytics, machine learning, and stock market analysis. Our mission is to empower businesses through data-driven insights and cutting-edge AI technologies. We are committed to pushing the boundaries of innovation to enhance decision-making processes and deliver tangible business results. Role Description We are looking for an experienced Machine Learning Expert to join our team. As part of this role, you will work on developing sports prediction models, utilizing machine learning techniques and data science methods to forecast outcomes in sports. This is an exciting opportunity to apply advanced ML algorithms in the sports domain. Key Responsibilities Develop and optimize machine learning models for sports prediction. Handle large datasets, clean and preprocess raw data for model building. Collaborate with cross-functional teams to implement models in real-world applications. Conduct experiments and refine models to improve accuracy and efficiency. Stay updated on the latest advancements in machine learning and sports analytics. Provide clear and actionable insights from model outputs to stakeholders. Required Qualifications At least 3 years of professional experience in machine learning, particularly in sports prediction. Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow, etc.). Experience in time-series forecasting, regression, classification, and other ML techniques. Familiarity with sports datasets, player stats, and historical performance data. Proven track record of developing and deploying machine learning models. Strong problem-solving abilities and analytical thinking. Ability to work independently and in a collaborative, remote setting. Preferred Qualifications Experience with sports prediction models or analytics. Familiarity with cloud platforms (AWS, Azure, Google Cloud). Exposure to deep learning and advanced machine learning techniques. Experience in model evaluation, tuning, and preventing issues like overfitting or data leakage. How to Apply To apply for this role, please share: A summary of your previous work in machine learning and sports prediction. Email at insightfusionanalytics@gmail.com Examples of sports prediction models or similar projects you’ve worked on (with links to any repositories or project summaries). Your approach to handling model challenges such as data leakage, overfitting, or bias.

Location: Remote | Commitment: Full-time Company Overview Insight Fusion Analytics turns complex data into actionable insight for clients across finance, retail, and professional sport. Our sports-analytics unit builds predictive systems that transform raw match, athlete, and biomechanical data into winning strategies. Role Summary We’re hiring a Lead Statistician with deep expertise in sports prediction to architect, validate, and continuously refine our forecasting engines. You’ll own the statistical core—from feature-engineering pipelines through probabilistic calibration—working with ML engineers and domain analysts to produce production-ready forecasts that thrive in real-world conditions. What You’ll Do Model Architecture & Validation – Design Bayesian and frequentist frameworks (hierarchical Elo, Poisson-Gamma, state-space models) and build leakage-proof cross-validation strategies. Feature Engineering & Experimental Design – Derive advanced spatio-temporal, biometric, and contextual features; run A/B and multivariate tests to quantify lift. Uncertainty Quantification – Produce calibrated predictive intervals, scenario simulations, and decision-theoretic metrics (Brier, CRPS, EVaR). Mentorship & Review – Set statistical standards, review code/notebooks, and mentor junior analysts. Stakeholder Communication – Translate complex statistical results into concise recommendations for coaches, product managers, and executives. Must-Have Qualifications 8+ years professional experience (or PhD + 5 years ) in applied statistics, econometrics, or quantitative social science. Documented track record building sports prediction systems. Expert proficiency with Python (NumPy, SciPy, Pandas, statsmodels, PyMC/Stan) and SQL; R a plus. Mastery of resampling methods, hierarchical models, time-series analysis, Monte-Carlo simulation, and causal inference. Proven success preventing data leakage and look-ahead bias in live pipelines. Strong communication skills for both technical and non-technical audiences. Nice-to-Have Familiarity with deep-learning frameworks (TensorFlow/PyTorch) for hybrid stat-ML architectures. Experience deploying models on AWS, GCP, or Azure using containerized workflows. Publications or conference talks in sports analytics (MIT Sloan, NESSIS, MathSport). How to Apply Send the following to insightfusionanalytics@gmail.com : CV highlighting sports-analytics projects and publications. Portfolio or repo links demonstrating end-to-end statistical modelling for sports prediction. A one-page brief describing your proudest predictive model: objective, methodology, error analysis, and business impact.