Job Description

JOB DESCRIPTION Role Proficiency: Independently provides expertise on data analysis techniques using software tools streamlining business processes and managing team Outcomes: Managing and designing the reporting environment including data sources security and metadata. Providing technical expertise on data storage structures data mining and data cleansing. Supporting the data warehouse in identifying and revising reporting requirements. Supporting initiatives for data integrity and normalization. Assessing tests and implementing new or upgraded software and assisting with strategic decisions on new systems. Synthesize both quantitative and qualitative data into insights Generating reports from single or multiple systems. Troubleshooting the reporting database environment and reports. Understanding business requirements and translating it into executable steps for the team members. Identify and recommend new ways to streamline business processes Illustrates data graphically and translates complex findings into written text. Locating results to help the clients make better decisions. Get feedback from clients and offer to build solutions based on the feedback. Review the team\'s deliverables before sending final reports to stakeholders. Support cross-functional teams with data reports and insights on data. Training end users on new reports and dashboards. Set FAST goals and provide feedback on FAST goals of reportees Measures of Outcomes: Quality - number of review comments on codes written Accountable for data consistency and data quality. Number of medium to large custom application data models designed and implemented Illustrates data graphically and translates complex findings into written text. Number of results located to help clients make informed decisions. Attention to detail and level of accuracy. Number of business processes changed due to vital analysis. Number of Business Intelligent Dashboards developed Number of productivity standards defined for project Manage team members and review the tasks submitted by team members Number of mandatory trainings completed Outputs Expected: Determine Specific Data needs: Work with departmental managers to outline the specific data needs for each business method analysis project Management and Strategy: Oversees the activities of analyst personnel and ensures the efficient execution of their duties. Critical business insights: Mines the business\'s database in search of critical business insights and communicates findings to the relevant departments. Code: Creates efficient and reusable SQL code meant for the improvement manipulation and analysis of data. Creates efficient and reusable code. Follows coding best practices. Create/Validate Data Models: Builds statistical models diagnoses validates and improves the performance of these models over time. Predictive analytics: Seeks to determine likely outcomes by detecting tendencies in descriptive and diagnostic analysis Prescriptive analytics: Attempts to identify what business action to take Code Versioning: Organize and manage the changes and revisions to code. Use a version control tool like git bitbucket. etc. Create Reports: Create reports depicting the trends and behaviours from the analysed data Document: Create documentation for own work as well as perform peer review of documentation of others\' work Manage knowledge: Consume and contribute to project related documents share point libraries and client universities Status Reporting: Report status of tasks assigned Comply to project related reporting standards/process Skill Examples: Analytical Skills: Ability to work with large amounts of data: facts figures and number crunching. Communication Skills: Communicate effectively with a diverse population at various organization levels with the right level of detail. Critical Thinking: Data analysts must look at the numbers trends and data and come to new conclusions based on the findings. Presentation Skills - reports and oral presentations to client Strong meeting facilitation skills as well as presentation skills. Attention to Detail: Making sure to be vigilant in the analysis to come to correct conclusions. Mathematical Skills to estimate numerical data. Work in a team environment Proactively ask for and offer help Knowledge Examples: Database languages such as SQL Programming language such as R or Python Analytical tools and languages such as SAS & Mahout. Proficiency in MATLAB. Data visualization software such as Tableau or Qlik or Power BI. Proficient in mathematics and calculations. Spreadsheet tools such as Microsoft Excel or Google Sheets DBMS Operating Systems and software platforms Knowledge about customer domain and also sub domain where problem is solved Additional Comments: The job description for the proposed ML Data Scientist role is below: Job title: Data Scientist This role requires understanding the full data science product lifecycle, including conceptualization, data engineering, model development and testing, and productization and monitoring. The specific modeling skillset will be varied, including use cases in more traditional use cases like classification and regression-based problems but could quickly branch into natural language processing and potentially more advanced neural networks and deep learning use cases. The individual we select for this role will be an integral part of our team, collaborating actively in developing Advantasure\'s AI strategy, seeking out new product opportunities, and advocating for product enhancements that will drive operational efficiencies. RESPONSIBILITIES Responsibilities are multi-disciplinary and include: Providing technical and quantitative analysis. Using computer technology, computer modeling, spreadsheet applications, software tools, and programming languages. Participating in and responsible for projects requiring advanced statistical analyses, innovative research, mathematical calculations, and technical skills. Preparing and delivering summary reports to the relevant or affected areas within the Company. Helps to determine what actionable steps can be taken based on the findings. Communicating and training users on model results. Developing custom, explainable models that enhance business processes to reflect corporate goals, experience, and current market conditions using pattern recognition, evolutionary computation, and machine learning algorithms. Documenting model requirements. Examining and analyzing data to determine the optimal modeling approach. Building and finalizing models using training, testing, and cross-validation data sets, sharing model results, and delivering conclusions. Supporting the creation, development, and maintenance of our models. Facilitating and presenting the communication of predictive model results to and across corporate entities, including creating appropriate documents (PowerPoint presentations, etc.). Participating in the development of annual budgets, goals, objectives, and systems. Leads implementation efforts for assigned predictive model projects. Performs ad hoc analysis to identify issues with existing models. This position description identifies the responsibilities and tasks typically associated with the performance of the position. Other relevant essential functions may be required. EMPLOYMENT QUALIFICATIONS EDUCATION Bachelor\'s degree in insurance, math, economics, statistics, or data science is required. Advanced degree in statistics, actuarial science, or applied mathematics preferred. As defined by the Company\'s learning philosophy, continuous learning is required. Certification or progress toward certification is highly preferred and encouraged. EXPERIENCE With proper education credentials, four plus years of research, modeling, or actuarial experience is required. Insurance experience is preferred. SKILLS/KNOWLEDGE/ABILITIES Expert knowledge of modeling software and data manipulation tool and techniques. Expert knowledge of statistical modeling and data mining techniques. Understanding of infrastructure needs for machine learning models. Direct experience with cloud platforms like Databricks and familiarity with distributed computing systems are preferred. Knowledge of Python and PySpark preferred. Strong database management skills. Knowledge of healthcare and health insurance. Insurance and underwriting techniques and agency and policyholders\' needs. Ability to establish workflows manages multiple projects, meet necessary deadlines, and work without supervision. Ability to apply the principles of independent logical thinking to define problems, collect data, establish facts, draw valid conclusions, and make actionable strategic recommendations. Ability to manage responsibilities as unexpected pressures/dilemmas arise. Ability to maintain confidentiality. Ability to work effectively as a member of a team. Excellent interpersonal, organizational, and communication skills.

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