Role Overview:

The role is in a hybrid mode of work, and we are looking for candidates based in both our Chennai and Gurgaon offices.

Key Skills Required:

- Python, Pyspark

- SQL

- Databricks

- Healthcare projects

- Good experience using AI tools and applications

- Healthcare analytics experience

- Azure cloud

- Exposure to GenAI, RAG, and LLMs is preferred

- Client-facing experience is required for this role

The role will be responsible for overseeing the data analytics team and acting as 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.) and large datasets.

- Experience writing and reviewing code in SQL and Pyspark; extreme attention to detail and quality.

- Good experience using AI tools and Databricks.

- Prior experience with clients.

Soft Skills:

- Very strong communication, initiative, comfort in asking for help, skill in coordinating across multiple teams, and a passion for learning new data and analytics.

Core Responsibilities:

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

- Ensure high-quality execution of products including:

1. Gather requirements and scope tasks for the sprints.

2. Keeping standards high, including defining acceptance criteria, testing plans, and code reviews.

3. Full code review for the data analysts.

4. Business and requirements review for non-data analysts.

- Own the team Agile ceremonies including:

1. Running them with skill and receiving ongoing coaching from our Agile leaders.

2. Realize value from these ceremonies by focusing on translating them into constant team improvement.

3. 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 engagements.

- Delivering insights based on complex data analysis within relevant verticals (insurance, health care, banking, etc.).

- Hands-on experience in data manipulation skills in SQL and 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 (Healthcare, Insurance, Banking, Telecommunications, Logistics).

- Familiarity with or exposure to cloud engineering (preferred).

- Ability to translate technical information to non-technical stakeholders and vice versa.

- Strong verbal and written communication skills.

- Actively seeks information to clarify customer needs to deliver a better experience.

- Acts promptly to ensure customer needs are fulfilled.

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 communicate with stakeholders.

- Excellent management, coordination, and communication skills.

Technical Skills:

- 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 Databricks, Azure Studio, Data Factory, etc. (preferred).

- Understanding of data science in patient health management, provider profiling, healthcare reporting, and other key healthcare technologies is beneficial but not required.

- Understanding of data science in fraud, operations, lifestyle, and behavioral environments is beneficial but not required.

Qualifications:

- Bachelors degree in engineering, Data Science, Statistics, Mathematics, or a related quantitative field.

- MBA graduate from a Tier-1 institute or a masters degree in a relevant field.

- Minimum 8 years of experience in data and analytics.

- Minimum 3 years of experience in leading analytical teams, project management, and stakeholder management.

Additional Key Skills:

- Stakeholder Management, Client Communication, Project Management, Problem Solving, Python, SQL, Storytelling, and Presentation Skills.