Data Analyst - Houston, Texas Long Term Contract - Potential for Direct Apply Now - Position will go FAST! Candidates MUST have at least 3 years’ of working experience in consulting, operations/analytics role Looking for a company and position that has growth potential and unlimited ways to contribute? Then this is the role for you! Our client is in the renewable industry and is looking to expand their team by bringing on a Data Analyst. In this role you will have the ability to really dig into this role contributing your intelligence around data that will enable the sales organization to evolve through having the most critical data and analytics to drive the performance of their business. If you want to be challenged and are looking for the job of your dreams - this could be it. Exceptional leadership who are innovative and forward thinking! The Data Analyst will be responsible for implementation and tracking of overall metrics for the company’s Customer Acquisition team and will report to the Director of Customer Acquisitions. The Data Analyst will (i) work closely with the individual sales and marketing managers to develop, implement, and track relevant metrics to aid in managing the day to day business (ii) work closely with the Director of Customer Acquisitions to track overall sales and marketing performance as it relates to budget and forecast (iii) develop pricing, customer acquisition, & propensity models to support key sales and marketing strategies. The ideal candidate loves data, programming, creative problem solving, and optimizing processes. Responsibilities: Develop, track, and automate reporting that aids Customer Acquisition team in managing sales and marketing programs Identify gaps in business processes that contribute to poor data integrity and recommend and initiate changes to fix appropriate business processes Responsible to create Data Warehouse solution that will aid in performing job duties Develop reporting package that is suitable for detailed deep-dives into the business all the way to executive level monthly reporting Apply statistical modeling or machine learning algorithms to optimize sales and marketing efforts for customer acquisition and retention Develop regression/propensity models for use with sales and marketing campaigns (Direct Mail, e-mail journeys) and retention campaigns (likelihood to cancel) Develop data visualizations that aid in communicating results Quantify the effects of various marketing levers Translate, communicate, and present results and recommendations to a non-technical audience Technical Skills: Have you done any interesting analytics projects for fun? We would love to see them! Statistical modeling and analysis skills Strong general programming skills Proficiency with R and Python SAS programming a plus Strong SQL skills / understanding of relational databases Excel guru Microsoft Power BI or other visualization packages preferred Additional Knowledge, Skills and Abilities: Ability to translate complex business issues into achievable analytical learning objectives and actionable analytic projects Ability to build various propensity models Ability to work well under pressure, remaining focused and calm in a fast-paced environment Ability to communicate information clearly, both orally and in writing Ability to interpret complex analytic results and develop practical business implications Strategic marketing mindset and firm understanding of key marketing and financial concept Keen attention to detail Ability to work as a team member in a fast-paced environment Demonstrated ability to learn and apply new technologies and new analytics models/techniques as needed Qualifications: Education: Bachelor’s Degree in Economics, Statistics, Finance, Computer Science, Engineering, Mathematics Advanced Degree in a quantitative field a plus Candidates MUST have at least 3 years’ of working experience in consulting, operations/analytics roles

The Insights & Analytics team is responsible for analyzing vast amounts of data to better understand and predict customer behavior that in turn informs business decisions and improves J.Crew Group customers’ experiences. Our team has a broad mandate, handling customer analysis across the entire organization and informing marketing, merchandising, planning, stores/field, budgeting and other financial decisions. The Manager position is responsible for designing an appropriate methodology, accessing and analyzing large amounts of data, and synthesizing findings into insights in customer behavior. The work takes the form of strategic ad hoc projects, as well as more routine reporting to measure the effectiveness of various tactics and tests. Responsibilities include: Regularly liaise with the marketing, loyalty, merchandising, and stores teams to understand their business needs and provide the right analyses/insights based on their key strategies and issues Field ad hoc requests for customer analysis, acting as an analytical thought partner to the business stakeholder, and assigning the appropriate analytical approach Conduct advanced customer analyses and arrive at compelling data conclusions, including but not limited to cross-shop, customer profiles and KPIs, and studies into customer loyalty, acquisition and retention trends Translate data findings/trends into actionable insights to better understand complex shopping behavior and present analytical findings in easy-to-understand presentations, making clear recommendations based on deep insights into the data Own, design, develop and distribute customer reports and dashboards that clearly track the effectiveness of strategies underway Build predictive models to improve profitability, growth, retention, customer lifetime value, and other key performance indicators for our business stakeholders Implement formal modeling processes from end-to-end including data gathering, data profiling, numerical model building, calibration, cross-validation, and launching in production Advise on experimental designs to ensure new business strategies are tested appropriately and without bias; assist stakeholders in parsing results, arriving at conclusions and advising on next steps, when needed Act as a subject matter expert on best practices in retail customer analysis Work closely with vendors as needed to ensure integrity of data and analyses being provided Liaise with our customer database provider as needed to ensure data is processed correctly and recommend any changes or updates to support the growing business needs The ideal candidate: Has excellent familiarity with analyzing transactional customer data Is analytical and curious, especially about how numbers can define company strategy Is an excellent oral and written communicator who can clearly tell stories based on insights into the data Understands the retail industry and the analyses common in the trade Has advanced project management skills and efficiently manages tasks to completion Has some degree of modeling experience or familiarity with CLV, churn, propensity, and multi-touch attribution models Is extremely detail oriented Has an entrepreneurial mindset and is comfortable with change and ambiguity Is eager to continually improve his/her analytical and technical skills Has a positive, can-do attitude and wants to be part of a critical team Education & Experience Requirements: Master’s degree preferred in a quantitative field At least 5 years’ previous work experience in retail / e-commerce Superior research, statistical, analytical, processing and mathematical skills with ability to structure and conduct analyses Strong proficiency in R, SQL and/or Python, Tableau and Microsoft Office Suite Working knowledge of AWS toolkit, including S3, Athena, Glue, and Sagemaker

The need to maintain our core Computer Science group is vital to provide the technical capabilities necessary to successfully execute NSA's mission. The increased complexity of supporting NSA's mission requires world class researchers, programmers, and developers who operate in teams in areas such as software engineering, information technology infrastructure, high performance computing, data science, architectures, computer security, and networking in order to design and develop advanced tools, techniques, and systems. Given the pace of technologies and myriad of adversaries in the cyber realm and foreign nation state actors, Software Engineers at the NSA develop the technologies and abilities to maintain our advantage in both national defense and information gathering. Software Engineers help collect data, extract value, route and manage at scale, build user interfaces, protect our systems, and identify and develop support infrastructure as a service provider to the Agency and Intelligence Community. As a Software Engineer, your responsibilities can include: creating applications that scale across an entire data center identifying and retrieving the most important pieces of information out of 100s of petabytes of data leveraging open source software integrating off-the-shelf and government developed software leading new advances in computer science and riding the bleeding edge of computing technologies: microprocessor-based advances beyond the horizon supercomputers signals processing (including analog control) user interfaces deep learning information security the design and implementation of encryption advanced algorithms The ideal candidate is someone with excellent problem-solving, communication, and interpersonal skills who is able to: work in a team environment to build software handle multiple assignments synthesize information to solve complex problems apply knowledge data structures and algorithms to software engineering problems develop, diagnose, and operate complex computer systems identify customer needs and validate product design deliver software that others WANT to use deal with conflict within a team Knowledge and experience in one or more of the following is desired: programming with a high-level language (e.g., C, C++, Java, python, ruby) building user facing services, middleware, and backend systems Full-stack development operating systems administration and advanced user functions, site reliability engineering computer networking (e.g., communication protocols, distributed systems, , Internet of Things, real-time systems, routing and switching) data spaces, data modeling, data analysis, storage design, and administration information retrieval, machine learning, artificial intelligence, statistics and analytics vulnerability analysis