Data Scientist / Machine Learning Engineer/ Data Analyst

Data Scientist skilled in ML, forecasting analytics, delivering production-ready insights across VR, healthcare & policy
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Work expectations

Status
Actively looking
Not looking
Open to new opportunities
Previously hired through SkillsRobin
Location
Melbourne
-
Open to relocating
Commitment
Full-time, Casual / Contract / Part-time, Join as a startup co-founder, Internship
Availability from time of offer
Immediately
Experience
1-2 years
 experience
Top 3 programming languages/frameworks
Python, R, MySQL
Also knows
Data visualisation Tableau, PowerBI
Preferred work environment
Hybrid, Fully remote, In the office
Strengths
My key strengths lie in building practical, business-focused data science solutions from end to end. I excel at data cleaning, feature engineering, statistical analysis, and developing machine learning models that are reliable, interpretable, and deployable. I am particularly strong in applied machine learning, including classification, forecasting, clustering, and computer vision, using tools such as Python, R, Scikit-learn, PyTorch, and SQL. I also have strong data visualization and storytelling skills, enabling me to communicate insights clearly to both technical and non-technical stakeholders. Companies should hire me for my ability to combine analytical depth with real-world impact I focus not just on model accuracy, but on delivering insights that support decision-making, efficiency, and measurable outcomes.
Interested in working involving
I’m looking for analyst , sales , business , data science related roles
Not interested in work involving

Other information
I bring a strong growth mindset, ownership mentality, and adaptability to every role I take on. I am comfortable working across the full data lifecycle from raw data to deployment ready insights and collaborating with cross-functional teams. In addition to my technical background, I have demonstrated leadership and teamwork through both professional roles and competitive sports, having represented my state at the national level. I am motivated to work in environments where data is used to solve real problems, and I am eager to contribute quickly while continuing to grow as a data scientist and machine learning engineer.
Able to work in Australia without visa sponsorship
Requires visa sponsorship to work in Australia

Pay expectations

Full-time
$
60000
per year
Casual / Contract
$
per hour
Pay is negotiable in exchange for equity
Pay is negotiable in exchange for equity
Pay is not negotiable in exchange for equity
Open to volunteering or working for equity only
Not interested in volunteering or working for equity only if joining as a co-founder

Referred by

  •  

Work experience

Proudest professional achievement
One professional achievement I am particularly proud of is leading an end-to-end data science initiative at NextXR Group that directly influenced product and business strategy. I unified multiple fragmented industry datasets, labeled simulator categories, and built clustering and Random Forest models to identify high-ROI simulator opportunities and skill gaps. The insights were presented to leadership as a clear roadmap, helping prioritize development and investment decisions. In parallel, I designed a VR market demand analysis pipeline by scraping SteamDB and Meta Quest APIs, forecasting genre trends, and visualizing engagement patterns using Plotly dashboards. This work improved marketing precision by approximately 30%. Additionally, I engineered an AWS Bedrock multi-agent workflow orchestrated through AWS Lambda that automated marketing processes and reduced API costs by 15%. This achievement reflects my ability to translate complex data into actionable, real-world outcomes — the kind of work I aim to continue in future data science and machine learning roles.

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Education

I am currently pursuing a Master of Science in Data Science at RMIT University, Melbourne (expected Aug 2026), where my coursework and projects focus on applied machine learning, statistical modeling, forecasting, data visualization, and real-world analytics.

I previously completed a B.Tech in Artificial Intelligence and Data Science from Sri Venkateswara College of Engineering, Chennai, graduating with a CGPA of 8.89. During my undergraduate studies, I built a strong foundation in machine learning, deep learning, computer vision, statistics, and data engineering.

My academic work includes large-scale statistical analysis of healthcare datasets, predictive modeling for heart disease and diabetes, deep learning projects using CNNs and PyTorch, recommender systems, and time-series forecasting. I have also published peer-reviewed research on CNN-based gender classification, presented at the 4th ICECCE Conference in Dubai.

My education combines strong theoretical grounding with extensive practical, project-based experience aligned with industry applications.

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