Job Responsibilities

• Development of statistical models and algorithms

• Conduct statistical analysis to gain insights from complex datasets, supporting data-driven decisionmaking efforts.

• Offer insights and observations to stakeholders, identify trends and measure performance

• Support the creation of value from data, assisting in translating data into meaningful business

• solutions.

• Gain proficiency in financial services domain concepts and regulations to support the development of

• statistical models and AI/ML solutions tailored for financial applications.

• Collaborate with experienced banking professionals to design and implement ML models that meet the

• unique requirements of financial institutions.

• Contribute to shaping the organization's AI/ML strategy with the support of senior team members.

• Participate in converting data science prototypes into scalable machine learning solutions for potential

• deployment.

• Support the design of ML models and systems, considering adaptability and retraining capabilities

• under the guidance of experienced team members.

• Participate in the assessment of ML system performance to ensure alignment with corporate and IT

• strategies, collaborating with experienced colleagues.

• Understand and use computer science fundamentals, including data structures, algorithms,

• computability and complexity and computer architecture.

• Strong proficiency in programming tools (such as Python, R, etc) for data manipulation, statistical

• analysis, and machine learning tasks is essential.

• Familiarity with big data frameworks, such as Apache Hadoop or Spark, and have a willingness to

• learn and grow their expertise in handling and analyzing large-scale datasets

• Utilize machine learning algorithms and libraries with hands-on experience.

• Support software engineering and design aspects of projects with mentorship from cross-functional

• teams.

• Contribute to end-to-end designs with support from experienced team members.

• Adapt communication for non-programming experts.

• Stay informed about the latest tools and techniques, engaging in continuous learning.

• Contribute to the evaluation of data distribution variations impacting model performance.

• Apply foundational analytical techniques to support business value through ML and AI.

• Familiarity with cloud computing concepts and basic experience in deploying data science solutions on

• cloud platforms

• Collaborate with the team, sharing ideas and insights.

• Assist in the development of ML roadmaps.

• Seek learning opportunities and contribute to knowledge-sharing within the team.

• Contribute to the achievement of the business strategy, objectives, and values as a valuable team

• member.

Minimum Experience Level

• MS/PhD in STEM or related technical discipline

• 3-7 years’ experience in a statistical and/or data science role

• Deep knowledge of machine learning, statistics, optimization, or related field

• Experience with R, Python, Matlab is required, programming in C, C++, Java

• Experience working with large data sets, simulation/ optimization, and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, Gurobi, Arena, etc.)

• Excellent written and verbal communication skills along with strong desire to work in cross functional teams

• Attitude to thrive in a fun, fast-paced start-up like environment

Technical / Professional Knowledge

• Data Mining

• Research and analytics

• Data Tools

• Data analysis

• Statistical Analysis

• data/ data structures

• Presentation Skills

• Problem solving skills

• Supervised Learning

• Unsupervised Learning

• NLP

• Deep Learning

• Feature Engineering/Selection