We are seeking an Early Career Data Scientist to join our engineering team and help solve complex, real-world problems using data, mathematics, and machine learning.At Syncrowin, you will work with large-scale datasets to develop uncover operational patterns, and support intelligent decision-making across energy, manufacturing, mining, and critical infrastructure.You will work closely with experienced AI engineers, data scientists, and domain experts, gaining hands‐on exposure to the entire machine learning lifecycle, from data exploration and experimentation to model validation and deployment.This role is ideal for a recent graduate or early‐career professional with solid analytical foundations, intellectual curiosity, and a genuine interest in applying data science to challenging real‐world problems.We value demonstrated ability, initiative, and a willingness to learn over years of experience.What you will doExplore, clean, analyse, and interpret large‐scale industrial and operational datasetsDevelop and evaluate statistical and machine learning models for forecasting, anomaly detection, and optimisationPerform exploratory data analysis and identify meaningful patterns in complex datasetsBuild data preprocessing, feature engineering, and model evaluation pipelinesWork with time-series, sensor, and operational data from real industrial environmentsDesign experiments, test hypotheses, and communicate findings clearlyCollaborate with AI engineers to improve model accuracy, robustness, and generalisationContribute to research, prototyping, and the development of new AI capabilitiesDocument methodologies, experiments, and model performanceWhat you will needBachelor's or Master's degree in Data Science, Computer Science, Mathematics, Statistics, Engineering, Physics, or a related quantitative discipline0–3 years of relevant experience, including internships, academic research,



or substantial personal projectsSound understanding of statistics, probability, linear algebra, and machine learning fundamentalsExperience using SQL to query and manipulate dataAbility to structure analytical problems and draw meaningful conclusions from dataStrong attention to detail and a methodical approach to experimentationCuriosity, initiative, and willingness to learn new technical concepts quicklyAbility to communicate technical findings clearlyGood to haveAcademic or project experience with forecasting, deep learning, or optimisationFamiliarity with PyTorch or TensorFlowExposure to cloud platforms, particularly AzureExperience with sensor data, IoT, energy systems, or industrial datasetsParticipation in research projects, Kaggle competitions, or open‐source contributionsUnderstanding of MLOps, model deployment, or data engineering fundamentalsExperience with mathematical modelling, operations research, or applied optimisationWork on real industrial datasets and problems with measurable operational impactGain hands‐on experience building AI solutions beyond academic exercisesLearn directly from experienced engineers and technical foundersContribute to projects across energy, manufacturing, mining, and critical infrastructureDevelop your skills across applied machine learning, data engineering, and production AITake ownership of meaningful technical work early in your careerWhat we offerCompetitive compensationOpportunity to participate in an Employee Stock Option Plan (ESOP)Mentorship and direct collaboration with experienced AI engineersHands‐on exposure to the full AI development lifecycleSmall, sharp team with no unnecessary layers or bureaucracyOpportunities for technical growth, research, and increasing ownershipSounds like you?
We welcome applications from recent graduates and early‐career candidates with strong technical potential.
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📌 Early Data Scientist (Hybrid) (Melbourne)
🏢 Syncrowin Software Solutions Pty
📍 Melbourne