Head - Data Science & Engineering Unit

Job Description

* Duties and Responsibilities - Duties & Responsibilities: Managing the End to End Capability & Creation of Data Sciences Capability based Initiatives across the Rural FD & Insurance units. This unit works primarily on creating viable and business driven capability which includes AI ML & Data Unit. The key areas of capability are the following. Manage all the Data MIS s Dashboard and other BIU requirements from Rural Insurance and FD business. Facility business team with data cuts and insights for the ADHOC requirements. Create insightful business dashboards providing insights helping them track critical business KPI s Creation of Data Science models with business consumerization Leading Cross functional engagements including business support functions like IT etc. Proactive Management/team management/building of skilled teams in BI ML & Data related programs BIU and Data Science Subject Matter Experience (algorithmic level) Creation and maintenance of data models solving for business use cases for offline and online utilization PRINCIPAL ACCOUNTABILITIES (Accountabilities associated with the job) Managing the End to End Capability & Creation of Data Sciences Capability based Initiatives across the Rural FD & Insurance units. This unit works primarily on creating viable and business driven capability which includes AI ML & Data Unit. The key areas of capability are the following. Manage all the Data MIS Dashboard and other BIU requirements from Rural Insurance and FD business. Facility business team with data cuts and insights for the ADHOC requirements. Create insightful business dashboards providing insights helping them track critical business KPI s Creation of Data Science models with business consumerization Leading Cross functional engagements including business support functions like IT etc. Proactive Management/team management/building of skilled teams in BI ML & Data related programs BIU and Data Science Subject Matter Experience (algorithmic level) Creation and maintenance of data models solving for business use cases for offline and online utilization , * SKILLS AND KNOWLEDGE (Minimum acceptable proficiency for this job which best indicates the education and/or experience requirements of this job and not the incumbent) Educational Qualifications Minimum 15 to 16 years of industrial experience in managing hands on BI, Data Analytics and business driven use cases. Strong educational background in mathematical, statistical and data science orientations (PhD (Computer Science, artificial intelligence, Data Mining, Mathematics, Statistics. ) PhD (computer science | data sciences with industrial experience) is mandatory Hands on experience in data science algorithms and working in medium to complex business problems is mandatory. Strong understanding of languages/tools such as SQL, Phyton and Power BI along with strong solution experience with Data Science technology implementation architecture is mandatory. Experience in advanced models (theory and implementation). Working with large open and cloud scalable platforms. Demonstrated proactive leadership in the management of fields of Data Science Capability is mandatory Strong techno-functional management working with business teams (on business use cases/ programs) Management of Data Science Teams which includes core data science engineers & partners @ algorithmic depth Strong architectural inclination and has participated/contributed @ core design levels with ability to manage /work on complex large projects is must Strong IT & Business interactions capability Strong hands-on nature (ability to understand-code (base level) / ability to tech mentor - must) for team members Strong team player with exceptional program management (execution). Self-driven & high ownership levels are key Constantly ahead of curve in latest Data Science related technologies and capabilities that are relevant to BFL/Business Ability to think understand complex business requirements and render them as prototype systems with quick turnaround time. Strong verbal and written communications skills are a must, as well as the ability to work effectively across internal and external partners/virtual teams. Strong team working and working with grounded collaborations (inter and intra teams). Well connected with eco-system for technology and data science. Diverse domain spread in Data Sciences is a must Capability must be referenceable

Keyskills :
power bicore datause casesdata miningquick turnaroundtechno functionalprogram managementbusiness requirementsartificial intelligencetechnology implementationmissql