Manager - Data Analytics

Job Description

The role will be responsible to oversee data analytics team and be the technical head of a global workforce across a multi-country team. The objective of the role is to ensure timely, robust, and accurate research, conception, delivery and ongoing monitoring of analytical products and frameworks. Effective communication between key stakeholders (actuarial, statistical, technology, and data teams) is vital to ensure delivery. Key requirements Must have exceptional data sense and prior experience in healthcare data analytics Strong experience with analytics products Prior experience with cloud environments (azure, aws, etc) & large datasets Experience writing and reviewing code in sql and pyspark; extreme attention to detail and quality Experience managing >=5 person teams Prior experience with clientsSoft skills: very strong communication, lots of initiative--but also comfortable asking for help, skill in coordinating across multiple teams, passion for learning new data and analyticsCore responsibilities include:Translate client's guidance on roadmap & key priorities into sprints, user stories, and requirements wikisEnsure high quality execution of product including:Gather requirements & scope tasks for the sprintsKeeping standards high, including defining acceptance criteria/testing plans plus code reviewReviewing the team's work:Full code review for the data analystsBusiness/requirements review for non-DAs Own the team Agile ceremonies includingRunning them with skill and receiving ongoing coaching from our Agile leaders within AH*Realize value from these ceremonies - focus on translating these ceremonies into constant team improvementScope: daily standup, backlog refinement, sprint kickoff, sprint review, retrospective, etcCommunicate with the client as part of IPP implementation Owning and executing distinct work streams within larger analytics engagement Delivering insights based on complex data analysis, within relevant verticals (insurance, health care, banking, etc.) Hands on experience in data manipulation skills in SQL/Python. Experience in exploratory data analysis and feature engineering Must have strong capabilities in problem solving, managing own work diligently, thoroughly documenting own work, succinctly communicating analysis process and outcomes, as well as effectively working with clients Basic understanding of at least one business area and its components (Healthcare, Insurance, Banking, Telecommunications, Logistics) Familiarity with / Exposure on cloud engineering (preferred) Ability to translate technical information to non-technical stakeholders and vice versa Strong verbal and written communications skills Actively seeks information to clarify customer needs to deliver better experience Acts promptly to ensure customer needs are fulfilled What skills do you need?Behavioral skills Exceptional leadership and communication skills across a wide range of stakeholders Ability to work cohesively in a team environment while balancing multiple priorities High level of attention to detail, resilience, enthusiasm, energy and drive Positive, can-do attitude focused on continuous improvement Ability to take feedback and constructive criticism to drive improved delivery Rigorous ability to solve complex analytical problems, optimize environments and communication with stakeholders Excellent management, co-ordination and communication skills Technical SkillsA deep understanding of the technical tools used in analytical domain is required as the bases for development of analytical products, as such the following core understandings are required: Practical experience in SQL, python, Power BI and advanced excel in the context of data exploration and manipulation. Knowledge of data science and solution architecture on the cloud -Azure cloud (preferred) Knowledge of cloud technologies such as data bricks, azure studio, data factory, etc. (preferred) Understanding of data science in patient health management, provider profiling, healthcare reporting, and other key healthcare technologies etc. is beneficial but not required Understanding of data science in fraud, operations, lifestyle, behavioral environment is beneficial but not required Qualifications Bachelors degree in engineering, Data Science, Statistics, Mathematics, or related quantitative field. MBA graduate from a Tier-1 institute or a masters degree in relevant field Minimum 5 years of experience in data and analytics Minimum 4 years of experience in leading analytical teams, project management and stakeholder management Additional key skills we are looking atStakeholder Management, Client Communication, Team Management, Project Management, Problem Solving, Python, SQL, Storytelling, Presentation Skills