Job Summary

The Data Scientist (Predictive Analytics Analyst) will use advanced data modeling, predictive modeling, and analytical techniques to interpret key findings from company data and leverage these insights into initiatives that will support business outcomes.

Essential Job Duties & Responsibilities

• Works to build and continuously grow predictive analytics data systems, processes, reporting, and ultimately people to optimize business operations, provide hypotheses and simulations of suggested changes and communicate data intelligence to the organization.
• Identifies solutions to business trends and problems through complex big data analysis.
• Anticipates future demands of initiatives related to people, technology, budget, and business and designs/implement solutions to meet these needs.
• Manages and optimizes processes for data intake, validation, mining, and engineering as well as modeling, visualization, and communication deliverables.
• Identify solutions by sprawling data sets and the business mindset to convert insights into strategic opportunities for our company

Experience, Education & Skill Requirements

Experience Needed:

• 5 years related experience in predictive analytics required, preferably in a financial industry
• 1-2 year’s supervisory experience strongly preferred
• Demonstrated experience translating  data into knowledge to address complex technical and strategic business needs

Education:

• Bachelor's degree in Mathematics, Statistics, or Economics. Master’s degree preferred

Skills & Abilities Needed:

• Basic mastery and commitment to the continuous development of personal performance around the job-specific and leadership competencies necessary for this role.
• Strong working knowledge of data mining principles: predictive analytics, mapping, collecting data from multiple data systems on-premises and cloud-based data sources.
• Strong SQL skills, ability to perform effective querying involving multiple tables and subqueries.
• Understanding of and experience using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations for business units.
• Experience and knowledge of statistical modeling techniques: GLM multiple regression, logistic regression, log-linear regression, variable selection, etc.
• Experience writing advanced code statements, models, and macros.  Knowledge of various statistical software required, especially open source languages, such as R.
• Experience working with and creating databases and dashboards using all relevant data to inform decisions.
• The ability to effectively work both independently as a contributor and collaboratively in a team is required.
• Excellent communication (oral and written).
• Strong mathematical, analytical, and problem-solving skills with an ability to leverage operational insights to drive solutions.
• Strong attention to detail and highly organized while focusing on work quality.
• Ability to establish priorities and meet deadlines.

Perks:

Market competitive salary, Provident Fund, Self Medical Insurance, and EOBI.

Timing :

5 days job with Flexible shift timing preferably in evening and night shift.