Senior Data Analyst
Gurugram, Haryana, India
Intellect
Asiaβs largest mental health platform serving 3.5 million members in 60+ countries. Access coaching, therapy, and a self-care app easily in seconds.We are on a mission to revolutionize mental health care through the power of data. As a Senior Data Analyst, you will play a critical role in transforming how mental health insights are generated, understood, and applied. By analyzing data from diverse sources, you will help shape personalized, evidence-based mental health solutions and contribute to making care more accessible, effective, and impactful for individuals around the globe.
- Data Analysis & Insights:
- Analyze large, complex datasets to identify trends, patterns, and actionable insights that inform mental health interventions and strategies.
- Develop and present data-driven recommendations to enhance mental health care delivery.
- Machine Learning Models:
- Collaborate with data scientists and engineers to design, build, and deploy machine learning models for predictive and prescriptive analytics.
- Support the development of algorithms to identify patterns in mental health data and optimize care pathways.
- Reporting & Visualization:
- Build and maintain dashboards and reports using tools like Tableau, Power BI, or similar to track mental health outcomes and initiatives.
- Provide real-time updates and performance tracking for key health and wellness metrics.
- Collaboration:
- Partner with cross-functional teams (e.g., Product, Clinical, Engineering, Revenue) to understand data needs and deliver actionable insights.
- Act as a mentor to junior analysts, guiding their professional development and enhancing analytical capabilities.
- Data Management:
- Clean, preprocess, and structure data for analysis, ensuring accuracy and usability.
- Ensure data quality and consistency across all reporting systems while adhering to privacy and security standards in health care data.
- Advanced Analytics:
- Strong ability to interpret data and present findings in a clear, actionable manner.
- Experience with predictive modeling, statistical techniques, and machine learning applications.
- Conduct statistical analysis, predictive modeling, and hypothesis testing to evaluate mental health program outcomes.
- Design and analyze A/B tests to support the optimization of mental health tools and resources.
Requirements
- Proficiency in SQL for data extraction and manipulation.
- Strong skills in Python, R, or other statistical programming languages.
- Experience with machine learning frameworks (e.g., TensorFlow, Scikit-learn, PyTorch) is a plus.
- Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker).
- Knowledge of cloud platforms like AWS, Google BigQuery, or Snowflake.
- Working knowledge of ETL processes.
- Exceptional problem-solving skills and attention to detail.
- Strong communication and storytelling skills to convey data-driven insights to technical and non-technical audiences.
- Ability to manage multiple projects and prioritize tasks effectively.
Benefits
- Work in a diverse environment with people from over 10 countries
- A generous leave policy
- Work flexibility
- Medical coverage
- Annual Wage Supplement (Bonus)
- Christmas Leave (The team takes the whole Christmas week off separate from our leave policy)
- Birthday Leave (1 day)
- Holidays off
- Quarterly mental health day off
- Mental health benefits (Premium access to our app!)
- Work-life balance and employee wellness
- Regular social events where we have non work-related fun
* Salary range is an estimate based on our AI, ML, Data Science Salary Index π°
Tags: A/B testing AWS BigQuery Data analysis Data management Data quality Data visualization Engineering ETL Looker Machine Learning ML models Power BI Predictive modeling Privacy Python PyTorch R Scikit-learn Security Snowflake SQL Statistics Tableau TensorFlow Testing
Perks/benefits: Career development Health care Medical leave Salary bonus Team events Wellness
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.