Habitat Energy is hiring for an fresher entry level Junior Data Scientist role in US

Position:

• Junior Data Scientist

Company:

• Habitat Energy

Location:

• Austin, Texas, United States

Job type:

• Full-time

Job mode:

• Hybrid (minimum 2 days onsite in Austin office)

Job requisition id:

• Not explicitly mentioned

Years of experience:

• Entry-level (0–3 years)

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Company description:

• Habitat Energy is an innovative, fast-paced technology firm operating at the intersection of renewable energy, advanced analytics, and real-time energy trading.

• With offices across Austin (USA), Oxford (UK), and Melbourne (Australia), the company is built on a global vision of accelerating the transition to clean energy systems.

• Their core business revolves around algorithmic trading and optimization for energy storage and renewable energy assets, delivering strong financial outcomes for clients.

• By leveraging cutting-edge technology, Habitat Energy plays a vital role in making renewable sources more viable and profitable.

• Their diverse team of 100+ professionals brings together talents from energy trading, data science, software engineering, and asset management to solve some of the most pressing problems in the energy sector.

• The company culture supports innovation, continuous learning, and collaboration, all while working toward a more sustainable and energy-efficient world.

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Profile overview:

• The Junior Data Scientist role at Habitat Energy is designed for candidates who are eager to work on impactful real-time data challenges in the energy sector.

• The position serves as a bridge between technical expertise and commercial strategy, offering the opportunity to contribute to both development and operations.

• The primary focus will be on supporting live battery optimization systems and enhancing predictive models to guide commercial decisions.

• This role is ideal for individuals looking to build a strong foundation in applied data science while making meaningful contributions to sustainable energy projects.

• A key aspect of the position involves frequent collaboration with cross-functional teams including commercial strategy and engineering units.

• Candidates will engage in end-to-end data workflows, from data cleaning and analysis to deploying models that impact real-world battery operations.

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Qualifications:

• A Bachelor’s degree in Computer Science, Data Science, Engineering, or a similar technical field is required.

• Strong command over Python, especially libraries commonly used in optimization and data science, such as cvxpy, pandas/polars, and gradient boosting libraries.

• Solid understanding of analytical thinking, with a deep interest in solving real-world problems through data.

• Willingness to dive deep into the dynamics of energy markets, especially the intricacies of battery systems and renewable integration.

• Effective communication skills, both written and verbal, with the ability to translate technical insights into business language.

• Proven ability to function in a collaborative environment, contributing across departments to push projects forward.

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Additional info:

• The job requires a strong interest in energy markets and sustainable technologies. While technical skills are important, the company values enthusiasm, curiosity, and a willingness to learn.

• Prior experience in renewable energy domains or working with optimization platforms such as CVXPY or Airflow is advantageous, but not mandatory.

• Habitat Energy encourages applicants from diverse backgrounds and welcomes those who may not meet every listed requirement but can bring unique value to the team.

• Employees benefit from a hybrid working structure, combining flexible work-from-home policies with in-office collaboration twice a week.

• Compensation is competitive, and there are opportunities for continuous professional development and growth.

• Candidates must either reside in Austin or be willing to relocate. Visa sponsorship is not available for this role.

• The work culture is designed to be supportive and engaging, with a focus on delivering meaningful, high-quality work in a team-first environment.

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Core Responsibilities:

• Carry out rigorous quality assurance checks, both on the technical implementation and the business logic behind energy optimization systems (BESS/DART).

• Conduct targeted data analysis to support business decisions and improve the performance of operational systems.

• Manage and oversee live battery optimization systems, ensuring minimal downtime and efficient functioning through proactive problem-solving.

• Collaborate with the commercial teams to build pricing models that reflect real-time market dynamics.

• Run experimental tests to validate hypotheses around predictive modeling strategies, and iterate based on outcomes.

• Apply data science techniques to identify patterns and propose actionable insights that can improve financial and operational performance.

• Stay updated on industry trends and integrate new market drivers into ongoing modeling strategies.

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Technical Skill Set (Must Have):

• Proficient in Python with experience in:

  • Data wrangling libraries (pandas, polars)

  • Optimization libraries (cvxpy)

  • Machine learning toolkits (pytorch, gradient-boosted trees)

• Strong foundational knowledge of statistics, numerical methods, and optimization techniques.

• Ability to write clean, maintainable, and well-documented code for both exploratory and production settings.

• Understanding of backtesting, real-time systems, and iterative model improvement cycles.

• Excellent debugging and problem-solving skills, especially for real-world, noisy datasets.

• Familiarity with operational systems and their maintenance, including the ability to troubleshoot and provide solutions quickly.

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Bonus/Preferred Skills:

• Experience in renewable energy or energy trading environments.

• Exposure to workflow orchestration tools like Apache Airflow.

• Understanding of infrastructure as code, such as Terraform.

• Background in deploying machine learning models in commercial applications or operational workflows.

• Previous involvement in interdisciplinary teams or startup-like fast-paced environments.

• Experience running large-scale simulations or optimizing systems with real-time constraints.

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Workplace Expectations:

• Must be present in the Austin office at least two times a week as part of the hybrid model.

• Should be located in Austin or ready to relocate without visa sponsorship support.

• Expected to take initiative and ownership of tasks, even at the junior level.

• Open communication, honesty, and team-centric mindset are highly valued.

• Strong alignment with Habitat Energy’s mission of enabling a clean energy transition through data-driven innovation.

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Career Growth Potential:

• This role sets a strong foundation for individuals seeking to grow into mid- or senior-level roles in data science, especially within energy and sustainability domains.

• There is ample opportunity to contribute to the design and development of systems with significant real-world impact.

• The work done in this role directly informs trading strategies, system efficiency, and energy sustainability metrics.

• Employees receive mentorship and exposure to multiple verticals like commercial analytics, trading platforms, and machine learning.

Please click here to apply.

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