Overview Do you enjoy solving problems, looking at problems through a different lens, and working closely with customers to innovate new solutions to complex problems? Do you jump with excitement at the opportunity to identify trends and provide unique business solutions? Do you want to join a team where learning about a new technology or solution is part of our work every day? Then, come join us! The Industry Solutions Engineering (ISE) team is a global engineering organization that works directly with customers looking to leverage the latest technologies to address their toughest challenges. We work closely with our customers’ engineers to jointly develop code for cloud-based solutions that can accelerate their organization. We work in collaboration with Microsoft product teams, partners, and open-source communities to empower our customers to do more with the cloud. We develop solutions side-by-side with our customers through collaborative innovation to solve their challenges. This work involves the development of broadly applicable, high-impact solution patterns and open-source software assets that contribute to the Microsoft platform. We are hiring a Principal Data Scientist to help drive high-impact engineering projects with our customers and their partners, transforming their missions using AI and other cloud-based solutions and services. Data scientists have data management and expertise in developing statistical techniques to analyze data and find patterns. You will be part of a cross-functional team of software engineers, data scientists, technical program managers, and designers who work side-by-side with high-impact and strategic customers and their engineers to build innovative solutions. As part of our team, you will thrive in working with a variety of technologies, not just Microsoft technology. You will solve exciting business problems, contribute to open source, and collaborate with Microsoft product teams. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Responsibilities - You will oversee data acquisition and ensure data is properly formatted and described. You’ll also coach engineers in data cleaning and analysis best practices, identify gaps in current data sets, and drive ethics and privacy discussions around data collection and preparation. - You will evaluate your team’s models and recommend improvements as necessary, drive best practices for models, and develop operational models that run at scale. You’ll also conduct thorough reviews of data analysis and modeling techniques, and identify and invent new evaluation methods. - You will research and maintain a deep knowledge of the industry, including trends and technologies, so that you can identify strategy opportunities and contribute to thought leadership best practices. You’ll also write extensible code that spans multiple features, and develop expertise in proper debugging techniques. - You will define business, customer, and solution strategy goals, and partner with other teams to identify and explore new opportunities. You’ll also commit to a customer-oriented focus by acknowledging their needs, and offer customer pragmatic solutions that align with their data capabilities. - You will embody our culture and values. Qualifications Required/minimum qualifications - Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience. Other Requirements - This position is not eligible for visa sponsorship. Candidates must have authorization to work in the United States that does not now or in the future require employer sponsorship.​ Additional or preferred qualifications - Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience. - 3+ years customer-facing, project-delivery experience, professional services, and/or consulting experience. #ISEngineering #WSS Data Science IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Job Description: Remitly’s vision is to transform lives with trusted financial services that transcend borders. Since 2011, we have been tirelessly delivering on our promises to people who send money around the world. Today, we are reimagining global financial services and building products that extend beyond traditional barriers to give customers access to more of the services they need, no matter where they call home. Join over 2,700 employees worldwide who are growing their careers with purpose and connection with our customers while having a positive impact on millions of people around the globe. About the Role: Under the supervision of the Engineering Manager, the Senior Data Scientist will serve as a core member of the data science team responsible for developing analytical models, machine learning algorithms, and data-driven insights to optimize customer acquisition, engagement, and profitability across the Company’s products. Telecommuting is available based on manager approval. You Will: - Analyze and extract insights from large, complex datasets using statistical and computational techniques. - Apply data mining and feature engineering methods to prepare datasets for modeling and experimentation. - Design, develop, and test statistical and machine learning models to optimize marketing performance. - Develop and implement algorithms to support computation, scoring, and decision-making. - Build and enhance analytical infrastructure and frameworks that support scalable, automated model deployment and continuous learning, as well as metrics-based A/B testing. - Present the results of complex analytics and modeling projects to business and non-technical audiences in clear, actionable terms. You Have: - Position requires a Master’s degree in Data Science, Business Analytics, Statistics, Computer Science, Information Science, Engineering or a related quantitative field and 2 years of experience with applying forecasting, measurement, and statistical and machine learning modeling techniques to solve business problems. - 2 years of experience with gathering business requirements and translating them into data-driven, measurable solutions. - 2 years of experience with performing statistical analyses to measure the impact of decisioning systems on key business metrics. - 2 years of experience with developing and implementing measurement frameworks to evaluate model performance and business outcomes. - 2 years of experience with developing dashboards to visualize data insights to resolve business problems. - 2 years of experience with performing root cause analysis and designing business process flows. - 2 years of experience with building prototypes and proof-of-concepts for new algorithms, model architectures, and data-processing approaches. - 2 years of experience with enhancing and deploying predictive models and decisioning systems to optimize performance and scalability. - 2 years of experience with using Airflow, Asana, AWS Glue, AWS Redshift, Azure, Big Data, Decision Trees, Git, Hypothesis Testing, K-Means, Linear Regression, Logistic Regression, Looker, MATLAB, Matplotlib, NumPy, Pandas, Power BI, Predictive Modeling, PySpark, Python, PyTorch, QuickSight, R, Random Forests, SAS, scikit-learn, Seaborn, Snowflake, SQL, Tableau, TensorFlow, VBA, and version control. Compensation Details. The starting base salary range for this position is typically $176,000.00 – $220,000.00 per year. In the U.S., Remitly employees are shareholders in our Company and equity is part of our total compensation plan. Your recruiter can share more information about medical benefits offered, as well as other financial benefits and total compensation components offered with this role. #LI-DNI #FB-DNI #IN-DNI #TW-DNI #GD-DNI Our Benefits: - Flexible paid time off - Health, dental, and vision + 401k plan with company matching - Paid parental, medical, military and family care leave - Mental Health & Family Forming Benefits - Employee Stock Purchase Plan (ESPP) - Continuing education and travel benefits We are committed to nondiscrimination across our global organization and in all of our business operations. Employment is determined based upon personal capabilities and qualifications without discrimination on the basis of race, creed, color, religion, sex, gender identification and expression, marital status, military status or status as an honorably discharge/veteran, pregnancy (including a woman’s potential to get pregnant, pregnancy-related conditions, and childbearing), sexual orientation, age (40 and over), national origin, ancestry, citizenship or immigration status, physical, mental, or sensory disability (including the use of a trained dog guide or service animal), HIV/AIDS or hepatitis C status, genetic information, status as an actual or perceived victim of domestic violence, sexual assault, or stalking, or any other protected class as established by law. Remitly is an E-Verify Employer Remitly is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Location: Indianapolis, IN Position Type: Remote Contract Length: 6 months + extensions Position Overview: This Data Scientist role is responsible for delivering actionable insights through advanced analytics, statistical modeling, and data science techniques, while supporting the development of scalable data solutions and tools. The position also serves as a key collaborator and mentor, partnering with stakeholders to translate business needs into data-driven strategies and fostering best practices across the organization. Duties: - Provide mentorship and guidance to junior Data Scientists and data-focused staff - Collaborate with stakeholders to understand business challenges and translate them into analytical solutions - Design, develop, and support internal web applications and interactive data tools - Analyze and assess data quality, structure, and integrity from various source systems - Partner with data engineers and BI teams to optimize data architecture, ETL processes, and reporting solutions - Develop rapid prototypes and minimally viable products to address user needs - Identify opportunities to improve processes and drive efficiencies using data science best practices - Perform data mining, statistical analysis, and modeling to generate actionable insights - Interpret and synthesize data from multiple sources using a range of analytical techniques - Maintain and manage code repositories using version control tools (e.g., GitHub) - Educate end users on interpreting and leveraging data insights effectively - Test, validate, and support enhancements to existing data solutions and systems - Provide ongoing maintenance and support for deployed data products - Document technical specifications and ensure alignment with established standards and best practices - Lead or support workshops, training sessions, and knowledge-sharing initiatives - Develop data visualizations and communicate findings to both technical and non-technical audiences - Build and deploy user-facing analytical applications using frameworks such as Shiny, Dash, Flask, or Streamlit Required Skills: - 2+ years of experience with a Bachelor’s Degree in analytics, statistics, computer science, informatics, mathematics, or a related field; or a Master’s Degree in a related field; or 4+ years of experience leveraging data to drive significant organizational impact - 2+ years of experience building user-facing applications using frameworks such as Shiny, Dash, Flask, or Streamlit, including connecting to backend data pipelines and deploying lightweight analytical tools - 2+ years of experience connecting to backend data pipelines and deploying analytical applications - 2+ years of experience using programming languages such as R, Python, and SQL to manipulate large datasets, generate insights, and develop automation solutions - 2+ years of experience applying advanced statistical techniques, including regression analysis, statistical testing, and distribution analysis - 2+ years of experience with data manipulation, including cleansing, standardizing, and transforming data - 2+ years of experience working with machine learning techniques such as clustering, decision trees, and neural networks - 2+ years of experience working with relational and dimensional databases, including their theories, principles, and best practices - Experience leading workshops or training sessions for user communities - Strong analytical, conceptual, and problem-solving skills - Experience creating and delivering data visualizations to diverse audiences - Demonstrated strategic thinking capabilities - Strong written, verbal, and presentation communication skills - Proven ability to be a resourceful, self-motivated team player - Ability to thrive in a fast-paced environment - Strong communication skills with the ability to understand and articulate complex problem nuances Preferred Skills: - Experience with geocoding and geospatial data - Experience with network diagramming and graph-based tools such as Neo4j - Experience working with containerization and orchestration tools such as Docker and Kubernetes - Additional experience with tools such as Shiny or similar advanced analytical frameworks

• Research and experiment with multifamily datasets to identify opportunities for new product features and pricing insights. • Partner with product managers and engineers to define requirements and design data-driven capabilities for ApartmentIQ's revenue management products. • Translate revenue management workflows into scalable tools and features — you should be able to sit in a pricing call and immediately understand what the revenue manager is trying to solve. • Apply LLMs and other AI techniques to accelerate research, automate workflows, and unlock new insights from structured and unstructured market data. • Design and run experiments to measure whether our data and recommendations actually drive better RM outcomes for customers. • Act as a subject matter expert on multifamily revenue management, ensuring the product reflects real-world operator needs. • Create clear documentation, dashboards, and analyses to communicate findings and product opportunities. • Stay current on multifamily industry trends, data sources, AI/ML advances, and pricing methodologies.