Experience Level: Senior
Position Overview:
Senior Data Scientist to join our team to solve some of the hard problems for our customers. Our client is on a mission to use data to the best in building products that they serve to their customers. We are looking for someone who has expertise in using ML/AI algorithms to improve our product in identifying customer pain points and corresponding solutions recommendation. The ideal candidate is expected to show strong business acumen and understand business problems, develop hypotheses and test the results to influence solution design. Have experience in understanding customer emotions and sentiments which will help you to apply and shape solutions. Should be hands on with various tools for data processing, analysis and visualization, programming languages and frameworks to derive meaningful insights. (Examples: Python, Spark, R, TensorFlow, PyTorch, AWS Kinesis, Redshift,etc).
Roles & Responsibilities:
- Develop Code
- Discuss with C-level leadership, Engineers, Product Managers to formulate hypotheses, solutions and desired outcomes.
- Act as Subject Matter Expert on ML, Data and AI statistical models and how they apply to business problems.
- You will help to implement models in Machine Learning, Optimization, Neural Networks, Artificial Intelligence (Natural Language Processing), and other quantitative approaches.
- Familiarity with Data Engineering techniques to gather, prepare, cleanse and transform data for analysis and AI automation, including data pipelines.
- Familiarity with getting data from social media - twitter, instagram, reddit, facebook, etc.
- Create prototypes, minimally viable products
- Deliver meaningful insights and predictions
- Demonstrate business value
- Mentor and coach others in the team
Must Have:
A Bachelor/Master/PhD degree in Computer Science Engineering/Data Science/ Operations Research/Statistics/or a related technical degree.
Overall 8+ years of working experience2+ years of hands-on working experience as Data Scientist with deep understanding of Machine Learning and AI algorithms- Linear Regression, Logic Regression, Decision Trees, K-Nearest Neighbors, Neural Networks, Random Forests, NLP/NLU, etc
1+ years of experience with different frameworks such as Tensor flow, PyTorch, Keros, SparkML.2+ years of hands-on coding experience with languages such as Python, R, Scala, Go, etc.
Good experience with source control systems such as git
Good to Have:
- Experience in microservices with container technologies like Docker/Kubernetes
- Working experience with deploying and running services in Kubernetes
- Experience with the AWS services (Examples: SageMaker, Comprehend, Lex, Rekognition, Transcribe, EKS, Lambda, S3, etc)
- Experience with troubleshooting production systems.
- Good understanding and use of CICD systems such as Jenkins, Gitlab, etc.
Location : Banglaore
About NomiSo:
NomiSo is a Product Engineering company currently focussed on Video Stream Engineering, backed by AI and ML. We are a team of Software Engineers, Architects and Cloud Experts with more than 100 years of combined expertise in Technology and Delivery Management.
Our mission is to Empower and Enhance the lives of our customers, through simple solutions for their complex business problems.
At NomiSo we encourage entrepreneurial spirit - to learn, grow and improve. A great workplace, thrives on ideas and opportunities. That is a part of our DNA. We're in pursuit of colleagues who share similar passions, are nimble and thrive when challenged. We offer a positive, stimulating and fun environment with opportunities to grow, a fast-paced approach to innovation, and a place where your views are valued and encouraged.
We invite you to push your boundaries and join us in fulfilling your career aspirations!
We are an equal opportunity employer and are committed to diversity, equity, and inclusion. We do not discriminate on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other protected characteristics.
