Data Analyst (Sleep Science Technology)
Fatigue Science is the leading provider of predictive human performance insights to mining, trucking, and heavy industry.We are looking for a dedicated Data Analyst to join our growing team. At Fatigue Science, we develop a SaaS platform that leverages Machine Learning and scientifically-validated biomathematical models to quantify and predict the effects of sleep disruption on reaction time and cognitive effectiveness – ultimately saving lives while increasing productivity for mine sites, trucking fleets, and other heavy industry organizations.
Growing 75% in the past year, we’re proud to have achieved product-market fit, and was recently recognized by the US National Safety Council with its 2022 Safety Innovation Award for our pioneering work in the field of Predictive Fatigue Management. We are a venture-backed organization of around 50 employees.
We are seeking a skilled professional who can work cross-functionally to bridge the worlds of business insights, data science, and machine learning. As a Data Analyst, you will be responsible for analyzing complex problems, extracting valuable insights from data, and providing strategic recommendations to drive informed decision-making and platform advancement. This role requires a unique blend of analytical thinking, statistical analysis, problem solving, creativity, and a curious mind.
- Perform data cleansing, manipulation, and integration tasks to ensure data quality and reliability for analysis.
- Conduct data analysis and interpretation to identify patterns, trends, and opportunities for improvements to our predictive fatigue and sleep prediction algorithms.
- Develop and apply advanced statistical and predictive models to support forecasting, optimization, and decision-making processes of platform and algorithm advancement.
- Utilize data visualization techniques to present findings and insights to stakeholders in a clear and compelling manner.
- Compile and present customer fatigue risk analyses related to site-wide, group level, or individual insights and trends.
- Collaborate with cross-functional teams to identify and define key performance indicators (KPIs), develop performance measurement frameworks and visualize results and trends
- Conduct research and stay up to date with emerging data science methodologies, tools, and technologies, and recommend their application as appropriate.
- Keep up to date on latest research findings in the fields of sleep science and fatigue monitoring.
- Contribute to the continuous improvement of data analytics processes, methodologies, and tools within the organization.
- Collaborate with stakeholders to gather and understand business requirements, translating them into actionable data-driven product solutions.
Skills and Qualifications
- Bachelor's or Master's degree in Statistics, Data Science, Computer Science, or a related field.
- Proven experience as a Data Analyst, Data Scientist, or a similar role, with a strong track record of delivering data-driven insights and recommendations.
- Proficiency in data manipulation, cleansing, and analysis using programming languages such as Python or R.
- Experience with data visualization tools, such as Data Studio/Looker, Power BI, or similar platforms.
- Strong knowledge of statistical analysis techniques, predictive modeling, and machine learning algorithms.
- Familiarity with database management systems and SQL for data extraction and manipulation.
- Excellent analytical thinking, problem-solving, and critical-thinking skills.
- Strong communication and interpersonal skills to effectively collaborate with stakeholders at all levels, including customers.
- Ability to work independently and as part of a team in a fast-paced and dynamic environment.
- Attention to detail and a commitment to delivering accurate and high-quality results.
- Familiarity with mining or transportation industries or understanding of sleep science space is a plus.
A flexible and cohesive work environment is offered. You will work with a dedicated team who thrive on learning from and mentoring each other.
We thank you for your interest in this position. Due to the high volume of applications we receive, only successful candidates will be contacted.