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Key Responsibilities:
- Design and implement Bayesian statistical models with priors, likelihoods, and posterior inference.
- Build Markov chain and Hidden Markov Model formulations for sequential and behavioral patterns.
- Apply MCMC methods, including Metropolis-Hastings sampling, to estimate posterior distributions.
Collaboration:
- Work alongside solution architect and client's CTO to align model design with platform architecture.
- Guide backend engineering on translating models into production service architecture.
- Partner with delivery and engineering leads to size and sequence statistical modeling initiatives.
Qualifications:
- Senior-level experience with strong background in Bayesian modeling, Markov chains, MCMC, mixture models, and Expectation-Maximization.
- Proficiency in Python or R with probabilistic/statistical libraries.
- Excellent written and verbal communication skills in English.
Software Mind
Software Mind is a team of engineers that support companies in ramping up their projects. The company offers an excellent work environment and is certified by Great Place To Work.