Scienaptic - Data Scientist

Data Scientist

About the Role :

We are searching for a strategic and inquisitive Data Scientist to Develop and run with Data- Centred Projects. The chosen Candidate will be responsible for Developing all aspects of Data mining, Predictive Analytics, Solution Development to name a few.

Requirements :

- Ability to Analyze complex Data and provide recommendations to Business.

- Proficient with Statistical Analysis, AI/ML Algorithms & applying them on Large Datasets.

- Establish Scalable, Efficient Solutions for large scale Data Analysis, AI/ML Model Development, AI/ML Model Validation, AI/ML Model Implementation and AI/ML Model Automation (MLOps).

- Excellent proficiency in Core Python Fundamentals, Python Programming, and other relevant Python Frameworks (such as Django, Flask etc.), Object Relational Mapper Libraries, SQL.

- Strong knowledge of AI/ML/DL Techniques, Algorithms, and tools with exposure to CNN, RNN (LSTM), Transformers (BERT).

- Experience with Training BERT, LSTM for different NLP tasks.

- Exposure to NLP Data Wrangling and Tokenization.

- Proficiency in working with Open-Source Deep Learning libraries like TensorFlow, Keras, Pytorch.

- Proficient in communicating technical findings to Non-Technical Stakeholders.

- Communicate Complex Data or Algorithms into simple Conclusions that will empower Leadership to drive action based on the Insights derived.

- Strong Presentation and Communication Skills.

Good to have :

- Exposure to Cloud Technologies like Azure, AWS or GCP

Education :

- Bachelor's/Master's degree in Engineering or any Quantitative discipline from Premier Institutes

About Us :

Scienaptic is on a mission to increase credit availability by transforming technology used in credit decisioning. Over 150 years of credit experience is embedded in Scienaptic' s AI native credit decision platform. Our clients across banks, credit unions, fintech, and other lenders use the platform to constantly improve the quality of underwriting decisions. This enables them to say 'yes' to borrowers more often and faster.