Job Summary:

• Run analyses, present and promote results to internal stakeholders and external clients and partners 
• Prototype ideas, run experiments and iterate in order to design data-driven solutions to business problems 
• Collaborate with Data Scientists to support and improve new and existing data products. 
• Attend client meetings and brainstorm sessions as subject matter expert on Dstillery technologies and capabilities 
• Create client-facing data stories for marketing collateral, white papers and case studies.   
• Screen and implement emerging prop-tech and data science platforms relevant to commercial real estate
• Build, interpret and update cash flow models, location analytic metadata, and sale/lease comps
• Research and report commercial real estate macroeconomic trends in Civitas’s target markets
• Research commercial office buildings and tenants in Civitas’s target markets
• Assist with operational and marketing team to design client-facing presentations using emerging technology
• Update commercial real estate records, listings, transaction comparables, and CRM database

Skills on Resume:

• Data Analysis (Hard Skills)
• Solution Design (Hard Skills)
• Client Communication (Soft Skills)
• Product Support (Hard Skills)
• Data Storytelling (Hard Skills)
• Technology Implementation (Hard Skills)
• Cash Flow Modeling (Hard Skills)
• Market Research (Hard Skills)

Job Summary:

• Build and promote data fueled outcomes that help improve financial health of members
• Provide insight into leading analytic practices, designs, and lead iterative learning and development cycles to produce analytic solutions that will become a part of the core deliverable for marketing outreach, targeted segmentation, and/or data driven decisions
• Work with organizational stakeholders to identify the business requirements and the expected outcomes
• Analyze new and existing data analysis systems and make recommendations to the Directors and Managers of the team
• Plan, create, and implement complex models and algorithms for defined features to drive analytical solutions throughout the organization
• Independently conduct advanced analysis and visualize exploratory analysis clearly and concisely to provide actionable insights, identify trends, and measure performance
• Utilize modern cloud technologies and employ best practices from DevOps/MLOps to produce enterprise quality production Python and SQL code with minimal errors
• Collaborate with a wide range of technical and business experts to communicate the design, functioning, and output of models, analysis, and solutions developed
• Call outside brokerage companies and third-party service providers for market data
• Assist with Civitas social media platforms and website

Skills on Resume:

• Data Outcomes (Hard Skills)
• Analytic Practices (Hard Skills)
• Business Requirements (Soft Skills)
• System Analysis (Hard Skills)
• Model Implementation (Hard Skills)
• Advanced Analysis (Hard Skills)
• Cloud Technologies (Hard Skills)
• Market Research (Hard Skills)

Job Summary:

• Accurately integrate customer data from a variety of organizational systems.
• Derive customer attributes and intents through novel uses of the data at hand and models to understand, describe and predict customer behaviour.
• Recommending and implementing changes to existing models and attributes to improve output quality.
• Implementing new models and attributes based on proof of concepts/logic defined by a Data Scientist.
• Understanding the business context in which their models operate to ensure model results are actionable.
• Executing and monitoring model validation workflows and notifying the Data Scientist/Manager when problems arise, providing production support 
• Working with operations teams to ensure model results/recommendations are fully understood and integrated into customer personalization processes.
• Working with the technology & infrastructure teams to productionize models and ensure that documentation and code storage standards are met.
• Providing ad hoc analytics and recommendations for action 
• Having a concrete understanding of data sources and data quality, based on relevant information from a Data Analyst.

Skills on Resume:

• Customer Data Integration (Hard Skills)
• Customer Behavior Analysis (Hard Skills)
• Model Improvement (Hard Skills)
• Model Implementation (Hard Skills)
• Business Context Understanding (Soft Skills)
• Model Validation (Hard Skills)
• Production Support (Hard Skills)
• Data Quality Assessment (Hard Skills)

Job Summary:

• Partner with Analyst teams and the Director of Product Engineering to continually improve the accuracy and relevance of elite models
• Work with the Project Manager to balance the model production workload so that client timelines are adhered to
• Develop the utilization of different modeling types that best fit a particular client’s situation and to keep it on the cutting edge
• Teach other analysts to build models by fostering a connectedness between the DS dept and the Analytics dept with the goal being for analysts to become ‘modelers’.
• Build tools and workflows designed so that an analyst can build models as well
• Teach analysts how to interpret the models they build
• Implement a stair-stepped approach, starting with the easier model types to the more complicated
• Focus on improving/productizing existing modeling methods
• Adding newer/more cutting-edge modeling methods to a suite of model types
• Developing interpretation for individual variable impacts in advanced modeling techniques for client communication and transparency

Skills on Resume:

• Model Improvement (Hard Skills)
• Workload Management (Soft Skills)
• Modeling Techniques (Hard Skills)
• Training and Mentorship (Soft Skills)
• Tool Development (Hard Skills)
• Model Interpretation (Hard Skills)
• Advanced Modeling (Hard Skills)
• Variable Impact Analysis (Hard Skills)

Job Summary:

• Oversee the continued development of the category level Index models, along with the tiers of customization that accompany them
• Work with the sales/business development teams to appropriately tailor these to the market
• Continue to work with Product Engineering Team to understand and develop new/improved methods for Variable Appending and Optimization in particular
• Productize and systemize modeling methodology by automating the processes so that they are repeatable and predictive
• Create guides on techniques employed during the modeling process. 
• Summarize key functions that drive sales/operations and how to quantify the value proposition
• Codify and implement QC process for the Data Science department
• Help improve model deliverables to keep them fresh and relevant by working with the Analytics Manager & Product Engineering Director
• Develop templates for the other model builders to use for model deliveries

Skills on Resume:

• Model Development (Hard Skills)
• Market Customization (Hard Skills)
• Variable Optimization (Hard Skills)
• Methodology Automation (Hard Skills)
• Process Documentation (Hard Skills)
• Value Analysis (Hard Skills)
• Quality Control (Hard Skills)
• Template Creation (Hard Skills)

• Proficient in developing models using techniques such as Logistic Regression, Linear Regression, CHAID, Cluster Analysis, Bayesian Algorithms, Neural Networks.
• Experienced in the use of Business Intelligence, Analytical and Statistical packages (e.g. SQL, SAS, R-Studio, Python)
• Excellent communication, interpersonal and listening skills. 
• Ability to present complex and detailed data in a simple to understand and innovative way
• A high level of customer focus with a proven record of delivering high standards of customer/seller service and experience
• Ability to work independently, proactively, multi-task (organised) and deliver.
• Able to work in teams, mediating between team members to diminish negative effects on team productivity and work environment
• Basic understanding of key commercial aspects of debt management

Qualifications: BA in Economics with 2 years of Experience

• Possess strong knowledge of R, Python and SQL and experience in building and scaling models for time series. 
• Strong expertise in Math/ Statistics, Machine Learning and Predictive Modelling (Regression, Neural Networks etc) 
• Ability to seamlessly navigate various programs and tools utilized as part of the collection process  
• Strong Knowledge of Regression/ Linear Analysis Familiarity with any Deep Learning, Distributed RF, Generalized Linear Model, K- Mean and naive Bayes Familiarity with designing algorithms on Hadoop ecosystem 
• Strong interpersonal and communication skills and are adept at working with multiple stakeholders to drive desired outcomes 
• Strong analytical skills and comfortable dealing with numerical data  
• Strong attention to detail and delivery of work that is of a high standard 
• Be a creative problem solver and can multitask in fast-paced environments 

Qualifications: BS in Data Science with 3 years of Experience

• Proficiency with Machine Learning model development, training, validation, and application
• Proficiency in mathematical disciplines including linear algebra, calculus, probabilistic models, and statistics
• Data manipulation techniques, including ETL/ETLV
• Experience developing in Java, .NET, and SQL languages
• Experience with R, Python, or Scala scripting techniques
• Experience with data visualization platforms like D3.js, Tableau, Kibana, HTML5, and CSS
• Competency in Graph/NoSQL database techniques, and RDBS platforms like Oracle and MS SQL Server
• Experience using and developing RESTful and SOAP Web Services
• General knowledge of software development practices and technical documentation (requirements, functional specifications, test plans, etc.)

Qualifications: BS in Statistics with 4 years of Experience

• Hands on experience in building data and analytics centric solutions using multiple Analytical languages(Python, R, Spark).
• Experience working on one or more of the Analytical Tools such as DataRobot, Dataiku, H2O3, Tableau, Arcadia, Microsoft R, Python – Sci-Kit Learn, PySpark, SparklyR
• Experience with big data technologies such as Hadoop, Hive and Spark
• Strong mathematics skills (e.g., statistics, algebra)
• Understanding of complete Software Development Life Cycle(SDLC) and Model Development Life Cycle (MDLC)
• Excellent written and verbal communication skills.
• Good team player interested in sharing knowledge and cross-training other team members and shows interest in learning new technologies and products.
• Ability to work in a matrixed environment and follow procedures, processes and policies.
• Experience managing vendor interactions for troubleshooting sessions, enhancement requests, and guiding vendor roadmaps to meet Citi standards and functional requirements.
• Self-starter who works with minimal supervision and is able to work in a team with diverse skills and geographies.

Qualifications: BS in Computer Science with 5 years of Experience

• Hands-on experience with data analytics, data modeling, and coding, experience building large data sets from multiple sources
• Ability to think conceptually and creatively about problems and solutions
• Strong interpersonal communication skills, verbal and written, required due to the nature and level of interaction with senior management
• Demonstrates ability to prioritize workload and ability to manage multiple projects while meeting deadlines
• Advanced level experience with Excel, PowerPoint, and other Microsoft Office programs
• Experience creating dashboards and visualization utilizing tools like Tableau or MicroStrategy Dossier
• Experience with business intelligence and reporting software like MicroStrategy
• Advanced SQL experience
• Basic understanding of iterative programming structures

Qualifications: BS in Mathematics with 3 years of Experience