Role Description To support the production and use of gender statistics across Asia and the Pacific, UN Women is implementing its flagship programme Making Every Woman and Girl Count (Women Count) across the region. Women Count aims to create a radical shift in how gender statistics are used, produced and promoted to inform policy and advocacy on gender equality. The consultant will support the implementation of Women Count activities pertaining to environment statistics and non-conventional data sources. In particular, the consultant is expected to support, under the leadership of the Women Count team in Asia-Pacific, the processing of microdata from surveys, geospatial sources, and other sources, to generate methodologically sound and internationally comparable estimates on gender and the environment to populate UN Women’s Gender and Environment Dashboard. The consultant is expected to deliver the following outputs: - Generate additional estimates on gender and the environment for all countries where data is available. - Ensure the estimates are accurate, timely and comparable. - Ensure the estimates are available on a dedicated space on the UN Women data hub. - Ensure all analytical notebooks are fully reproducible, clearly documented, and aligned with best practices in data transparency and reproducibility. Qualifications - Master’s Degree in statistics, mathematics, economics, social sciences, demography, development studies or related fields. - A first-level university degree in combination with two additional years of qualifying experience may be accepted in lieu of the advanced university degree. Requirements - A minimum 2 years of work experience conducting advanced analysis of microdata from individual level surveys, and integrating big data sources, including geospatial data, in line with international statistical standards. - Expert level proficiency in Stata and R, including statistical analysis and microdata processing. - Demonstrated experience creating high-quality graphs, statistical tables and other statistical outputs. - Strong expertise in developing reproducible research outputs (using R Markdown and/or Quarto). - Good understanding of geospatial data, formats and libraries (e.g. sf, leaflet). - Basic knowledge of Git and platforms and Github/Gitlab. - Knowledge on gender, environment and related social and economic issues. - Experience working with a United Nations Agency on data analysis and statistical reporting is highly desirable. - Fluency in English is required. Benefits - This is a home-based consultancy. - Official travel may be expected, processed by UN Women, following the duty travel policy. Company Description UN Women, grounded in the vision of equality enshrined in the Charter of the United Nations, works for the elimination of discrimination against women and girls; the empowerment of women; and the achievement of equality between women and men. It leads and coordinates United Nations system efforts to ensure that commitments on gender equality and gender mainstreaming translate into action throughout the world.

Role Description We are seeking a highly organized and detail-oriented Administrative Clerk to join our dynamic team. This role is crucial in ensuring the smooth and efficient operation of our office, providing essential support to various departments and contributing to a productive work environment. The ideal candidate will be a proactive problem-solver with excellent communication skills and a strong commitment to accuracy. This position offers a fantastic opportunity for an individual to grow their administrative career within a supportive and collaborative workplace environment. If you are a self-starter with a 'can-do' attitude, we encourage you to apply. This role is integral to our operational efficiency and provides a valuable opportunity to contribute to a thriving business in the Indian market. - Manage and maintain comprehensive physical and digital filing systems, ensuring accuracy and easy retrieval of documents. - Prepare and edit a variety of documents, including reports, presentations, and correspondence, with a keen eye for detail and grammar. - Handle incoming and outgoing communications, including managing emails, answering phone calls, and directing inquiries to appropriate personnel. - Schedule and coordinate meetings, appointments, and travel arrangements for team members as required. - Assist with data entry tasks, ensuring information is recorded accurately and efficiently into company databases and systems. - Order and maintain office supplies, ensuring adequate stock levels and managing vendor relationships effectively. - Provide general administrative support to various departments, contributing to the overall operational efficiency of the office. - Assist in the preparation of regular reports and summaries as requested by management. Qualifications - High school diploma or equivalent; a bachelor's degree or diploma in a related field is a plus. - Prior experience with office management software or ERP systems is advantageous. - Familiarity with basic accounting or bookkeeping principles is a benefit. - Ability to adapt to new technologies and processes quickly. Requirements - Proven experience in an administrative or clerical role, preferably within a fast-paced corporate environment. - Proficiency in Microsoft Office Suite (Word, Excel, PowerPoint, Outlook) and comfortable with various office software. - Excellent verbal and written communication skills with a strong command of English. - High level of accuracy and attention to detail, particularly in data entry and document preparation. - Ability to multitask, prioritize workload, and manage time effectively to meet deadlines. - Strong organizational and problem-solving skills. - A professional and positive attitude with the ability to work independently and as part of a team. Company Description

Role Description Brandeis University’s Online Health Informatics Program is seeking an Adjunct Faculty member for RHIN 151 Clinical Data Science and Machine Learning for the Fall-1 2026 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Health Informatics. This course will review methods for: - Preprocessing clinical data - Handling censoring and missingness - Model development and validation in healthcare contexts - Calibration - Subgroup fairness - Clinical utility assessment It will provide a comprehensive understanding of how clinical data science and machine learning impact healthcare data in addition to guidance on programming methods to process data. Basic programming skills (Python or R) and knowledge of statistics are strongly recommended prior to enrollment in the course. Qualifications - Advanced degree (Master’s or Ph.D.) in Data Science, Computer Science, Health Informatics, or a related field. - Minimum of 5 years professional experience in an analytics or leadership role with a focus on machine learning and using data science to improve healthcare outcomes. - Strong knowledge of statistical analysis, programming languages (e.g. Python, R), and data management. - At least 1 year of teaching or training experience (preferably online/asynchronous). - Experience with online instruction. - Excellent communication and teaching skills in an online learning environment. Requirements - Prior online teaching experience at the graduate level (preferred). - Knowledge of global learner personas and culturally responsive pedagogy (preferred). - Familiarity with Moodle LMS and digital authoring tools (e.g., H5P) (preferred). Benefits - Compensation for this position is $6573.15. Application Process Interested candidates should submit: - A cover letter highlighting relevant qualifications and teaching experience. - A current CV or resume. - Contact information for three professional references. Application review begins 5/27/2026 though we will continue to accept submissions on an ongoing basis. Equal Opportunity Statement Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").

Role Description Brandeis University’s Online Applied Data Science and Decision Analytics Program is seeking an Adjunct Faculty member for RADS 115 Data Engineering and Cloud Pipelines for the Fall 1 2026 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Applied Data Science and Decision Analytics. This course will explore concepts of data architecture, ETL/ELT design, and streaming analytics, including modules on sustainable data centers and carbon-efficient computation. Core Course Responsibilities Summary - Course Logistics and Facilitation: Focuses on the organized and timely rollout of course content, maintaining consistent communication through weekly announcements, and ensuring all instructional activities occur within university-approved digital platforms. - Instructor Presence and Engagement: Centers on building an active teaching persona by hosting live introductory sessions, facilitating weekly academic discourse in forums, and maintaining regular availability for student consultation. - Individual Feedback and Grading: Emphasizes the professional obligation to provide transparent, rubric-based evaluations and supportive commentary on student work within a standardized weekly timeframe. - Professional Conduct and Standards: Requires adherence to university communication protocols, the promotion of respectful online "netiquette," and ensuring the course meets accessibility and technical visibility standards before and during the term. Qualifications - Advanced degree (Masters or Ph.D) in Computer Science, Data Science, Information Systems, Software Engineering, or related field. - Industry Experience: Building or Managing Cloud Data Platforms. - Experience in Data Engineering and Cloud-Based Data Pipelines, including data architecture and data reliability. - At least 1 year of teaching or training experience (preferably online/asynchronous). - Experience with online instruction. - Excellent communication and teaching skills in an online learning environment. Requirements - Prior online teaching experience at the graduate level (preferred). - Knowledge of global learner personas and culturally responsive pedagogy (preferred). - Familiarity with Moodle LMS and digital authoring tools (e.g., H5P) (preferred). Benefits - Compensation for this position is $6573.15. - Pay Range Disclosure: The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements. Equal Opportunity Statement Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").