• Develop and execute sales strategies to achieve company revenue targets and expand client base within the data center power infrastructure sector. • Conduct thorough market research to identify potential clients, industry trends, and competitive landscape across the data center and critical power supply chain (hyperscalers, colocation providers, utilities, and EPC firms). • Identify, target, and acquire new clients among data center operators, hyperscalers, colocation providers, and the utilities/EPCs that build and power their campuses. • Build and maintain relationships with key decision-makers and stakeholders — including facilities, electrical engineering, and reliability teams — within target organizations. • Lead and manage the entire sales cycle, from initial contact to sales negotiations and closure, working together with the Power and Industrial sales teams. • Attend industry conferences, trade shows, and networking events to promote products and services and establish industry connections. • Develop and nurture long-term relationships with clients to ensure customer satisfaction and repeat business. • Prepare and deliver compelling presentations, proposals, and product and technology demonstrations to prospective clients. • Collaborate with the global marketing team to develop sales materials, case studies, and other promotional content. • Work closely with the global product management and development, regional marketing, and customer support teams to ensure alignment and support for business development activities. • Monitor and report on sales metrics, pipeline status, and business development activities. • Analyze and assess the effectiveness of business development strategies and make data-driven recommendations for improvement.

• Conduct fast-paced quantitative analyses in response to pollution episodes, energy market developments and other policy-relevant events, identifying impactful and policy-relevant findings. • Integrate, clean and analyse diverse proprietary, in-house and open datasets. • Produce reproducible code, robust methodology documentation, and reusable datasets. • Develop clear and effective data visualisations that communicate analytical insights. • Support research by combining quantitative analysis with domain expertise and desk research. • Develop new datasets, analytical tools and data products to strengthen CREA's research capabilities. • Work closely with colleagues to shape research questions and identify the most important analytical findings. • Contribute to reports, briefings and other research outputs by ensuring analyses are robust, transparent and reproducible.

• Responsible for mining big data, interpreting and analyzing complex data sets • Develops and deploys predictive models to analyze company performance and improve customer experiences • Applies statistical techniques and machine learning algorithms to identify trends within Mazda data • Collaborates closely with data engineers, analysts, and business stakeholders to integrate data-driven solutions

Role Description We are actively seeking a Data Scientist, Senior-Enterprise DS & AI Org for one of our clients. The role is remote and only available for W2 candidates. - Computer vision model experience is a must. A detailed write-up on experience with computer vision models is required. - Ability to synthesize complex information into clear insights and translate those insights into decisions and actions. - Demonstrated ability to explain technical concepts including but not limited to: - Statistical inference - Machine learning algorithms - Software engineering - Model deployment pipelines - Competency in the mathematical and statistical fields that underpin data science. - Ability to develop, coach, and teach career-level data scientists in data science, artificial intelligence, and machine learning techniques and technologies. - Strong in Python & R. Qualifications - Minimum: Bachelor's degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics, Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field. - Desired: Master's degree in one of the above areas. Requirements - Minimum: 4 years in data science (or 2 years if possessing a master's degree). - Demonstrated knowledge of and abilities with data science standards and processes (model evaluation, optimization, feature engineering, etc.) along with best practices to implement them. - Competency in software engineering, statistics, and machine learning techniques as they apply to data science deployment. - Competency in commonly used data science and/or operations research programming languages, packages, and tools. - Hands-on and theoretical experience of data science/machine learning models and algorithms. - Mastery in systems thinking and structuring complex problems. - Desired: experience building computer vision models. - Desired: experience with AWS technologies (S3, GroundTruth, Sagemaker). Company Description Rootshell Enterprise Technologies Inc. is a recognized provider of professional IT Consulting services in the US.