ACCOUNTABILITIES KEY PERFORMANCE INDICATORS
1. Undertake preprocessing of structured and unstructured data.
2. Analyze large amounts of data to discover trends and patterns.
3. Build predictive models using statistical and machine learning/deep learning algorithms to help business make effective data driven decisions.
4. Combine models through ensemble modeling.
5. Present insights using data visualization tools and make realistic stories to recommended support business frameworks.
6. Propose solutions and strategies to business challenges.
7. Link present customers’ data to forecast and predict future consumption for product efficiency and formulation.
8. Collaborate with stakeholders to build and improve products for segmented market or sector with data centric preference under uncertainty.
- Income/revenue generated based on insights from models and data solutions
- % of cost savings due to data-driven automations
- Customer Satisfaction rating (iNPS)
- Quality of data availability
- E-Learning scores
PROCESS & OTHERS:
- No. of models and/or data-related solutions developed and deployed per quarter
- No. of business insights delivered per quarter
RISK & CONTROL:
Internal Audit rating
- Business Acumen
- Conceptual/Analytical skills
- Data Wrangling & Visualization
- Confidentiality, Professionalism & Integrity
- Records management
- Technology savvy
- Stakeholder Management
- Research Orientation
- Quality assurance
- Business Analysis
- Business presentation skill
- R/Python and SQL Skills
- Problem Solving Skills
- Business Communication
- Presentation Skills
- Research Skills
- Understanding of The Organization’s
Business Orientation & Objectives
- Interpersonal Relations
- Decision quality & Problem solving
- Time & Self-Management
- Attention to Detail (Excellence)
- Continuous Learning
- Drive for Results (Efficiency)
- Customer focus
PERSON SPECIFICATION/JOB PROFILE
- The Job role is specialized and technical in nature. Thus, the holder should be versatile and have decent experience of collection, cloud technology (Azure) and analysis complex data critically, mathematically, and statistically. The individual should have worked with big data, machine learning, and AI technologies. He must be visionary, and research minded.
- The Job holder must possess strong analytical and problem-solving skills, excellent communication, and interpersonal skills, as well as possess ability to clearly explain things in front of technical/non-technical persons.
- The Job holder should have ability to work alone and within a team, be punctual and have time management skills.
- The Job holder should have ability to handle stress. He should be active, self-motivated, a quick learner, and innovative.
- The ideal candidate would also possess a background in database design, ETL processes (SSIS) and SQL analysis (SSAS) to assist the Analytics team in formalizing their internal data flows and related reporting processes.
- Be flexible enough to jump in and act as a team-member, taking immediate ownership of unanticipated scenarios, and responding to ad hoc database requests. To that end, the candidate must be comfortable writing SQL queries, stored procedures and triggers
- The candidate must demonstrate high energy/creativity, a passion for analyzing highly complex data sets, strong communication and project management skills, strong debugging skills, an entrepreneurial spirit, a relentless customer-focus, a practical understanding of quantitative methods, and superb attention to detail.
- Master's degree in Statistics, Operations Research, or Machine Learning (Ph.D. preferred)
- Minimum of 6-7 years' related work experience. Proven ability to use modeling, optimization, machine learning or text classification algorithms. C#, ASP, .NET languages, Data Warehouse and understanding of XML data structures are a plus.