Overview:

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 clients

Soft 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 analytics

Core responsibilities include:

- Translate client's guidance on roadmap & key priorities into sprints, user stories, and requirements wikis

Ensure high quality execution of product including:

- Gather requirements & scope tasks for the sprints

- Keeping standards high, including defining acceptance criteria/testing plans plus code review

Reviewing the team's work:

- Full code review for the data analysts

- Business/requirements review for non-DAs

- Own the team Agile ceremonies including

- Running 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 improvement

- Scope: daily standup, backlog refinement, sprint kickoff, sprint review, retrospective, etc

- Communicate 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 Skills:

A 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:

- Bachelor's degree in engineering, Data Science, Statistics, Mathematics, or related quantitative field.

- MBA graduate from a Tier-1 institute or a master's degree in relevant field

- Minimum 4 years of experience in leading analytical teams, project management and stakeholder management

Additional key skills we are looking at:

Stakeholder Management, Client Communication, Team Management, Project Management, Problem Solving, Python, SQL, Storytelling, Presentation Skills