Lead Data Scientist | ML Engineer

at  Reqiva Ltd

EXPERIENCE:

As a Lead Data Scientist, you will take ownership of developing data strategies, designing machine learning models, and delivering scalable analytics solutions. You will collaborate with cross-functional teams, contribute to product innovation, and mentor team members, driving our mission to mitigate risks in agriculture.

EXPERIENCE REQUIRED:

• Master’s or Ph.D. in Data Science, Machine Learning, Statistics, Computer Science, or a related field.
• 5+ years of hands-on experience in data science, with a strong focus on AI/ML and geospatial analysis.
• Expertise in Python and frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Strong proficiency in machine learning, predictive modeling, and statistical analysis.
• Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies.
• Knowledge of remote sensing data, time-series analysis, and geospatial systems.
  This position offers the chance to work at the intersection of data, sustainability, and innovation.
  You will have the chance to directly impact the growth of this start-up and shape the future of climate technologies. This is a Sydney based, hybrid role.
  Please apply for immediate consideration

ABOUT THE ROLE:

This position offers the opportunity to join a growing Climate-Tech business innovating the space by leveraging advanced analytics, machine learning, and domain expertise.
They are seeking a Lead Data Scientist | Senior Data Scientist to spearhead their data initiatives, build impactful models, and lead technical efforts to address climate risk challenges.

KEY RESPONSIBILITIES:

• This includes shaping the data science roadmap, staying informed on market trends in climate modelling and agricultural technologies.
• Build predictive models and analytics tools.
• Lead the development of machine learning algorithms, geospatial analyses, and advanced analytical methods.
• Ensure the quality, integrity, and security of data used in all initiatives.
• Work closely with product and engineering teams to deliver scalable solutions.
• Mentor and guide junior data scientists to foster a culture of collaboration and continuous learning.
• Provide technical oversight and drive best practices within the team.