:

Advanced degree in an analytical field (e.g., Data Science, Computer Science,

Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands on work experience in the space

- 3.5 - 7 Years of relevant experience in the space
- Expertise in mining AI/ML opportunities from open ended business problems

and drive solution design/development while closely collaborating with engineering, product and business teams
- Strong understanding of advanced data mining techniques, curating, processing

and transforming data to produce sound datasets
- Create outstanding data stories with expertise in robust EDA and statistical inference.

Experience in Experimentation design a big plus but should understands fundamentals of A/B testing
- Strong understanding of the Machine Learning lifecycle - feature engineering,

training, validation, scaling, deployment, scoring, monitoring, and feedback loop.

Exposure to Deep Learning applications and tools like TensorFlow, Theano, Torch,

Caffe is a big plus

- Experience with analytical programming languages, tools and libraries (Python a

must) as well as Shell scripting
- Very proficient is SQL and other relational databases. Proficient in PySpark.

Experience in using NoSQL databases. Candidate who is able to handle unstructured data with ease preferred
- Experience in working with AWS/Azure/GCP ecosystems. MLOps tools

experience a plus
- Good understanding of programming best practices and building code artifacts

for reuse. Should be comfortable with version controlling and collaborate comfortably in tools like git
- Ability to create frameworks that can perform model RCAs using analytical and

interpretability tools.



Should be able to peer review model documentations/code bases and find opportunities
- Experience in end-to-end delivery of AI driven Solutions (Deep learning ,

traditional data science projects) a big plus
- Solid communication, partnership and teamwork skills
- Ability to work in an extremely fast paced environment, meet deadlines, and

perform at high standards with limited supervision
- A self-starter who is looking to build grounds up and contribute to the making of

a potential big name in the space
- Experience in Banking and financial services is a plus. However, sound logical

reasoning and first principles problem solving are even more critical A typical day in the life of the job role:
1. As a key partner at the table, attend key meetings with the business team to

bring in the data perspective to the discussions
1. Perform comprehensive data explorations around to generate inquisitive

insights and scope out the problem
1. Develop simplistic to advanced solutions to address the problem at hand. We

believe in making swift (albeit sometimes marginal) impact to business KPIs and hence adopt an MVP approach to solution development
1. Build re-usable code analytical frameworks to address commonly occurring

business questions
1. Perform 360-degree customer profiling and opportunity analyses to guide new

product strategy. This is a nascent business and hence opportunities to guide business strategy are plenty
1. Guide team members on data science and analytics best practices to help

them overcome bottlenecks and challenges
1. The role will be an approximate 60% IC – 40% leading and the ratios can vary

basis need and fit
1. Develop Customer-360 Features that will be integrated into the Customer

Data Platform (CDP) to enhance the single view of our customer

📌 Data Scientist (Bengaluru)
🏢 Acura Solution
📍 Bengaluru