Data Scientist

4 days ago

Pune, India ACL Digital Full time

Technical skills and

competencies


The role translates into understanding the data to implementing the

data science/ML solutions and deploying it in production. You will

work as part of a cross-functional team (product manager, ML

engineer(s), ML platform engineer(s), backend, frontend, and QA) to

directly have an impact on business objectives.


Requirements and Skills

● 4-5 years of relevant experience

● Training/Certification in Data Science/Machine Learning is

preferred

● Ability to effectively work with technical leads

● Strong communication skills, ability to synthesize conclusions

● Familiarity with Data Science concepts, Machine Learning

algorithms & Libraries such as Scikit-learn, Numpy, Pandas, Stattools,

Tensorflow, PyTorch, XGBoost

● Worked in Machine Learning Training and Deployment

pipelines

● Worked in FastAPI/Falsk framework

● Worked in Docker and Virtual Environment

● Worked in Database Operations

● Strong analytical and problem solving skills

● Ability to thrive in a dynamic environment where there can be

degrees of ambiguity


Candidate Profile and

Competencies


Key Responsibility

● To be able to apply data mining, quantitative analysis,

statistical techniques and conduct simultaneous experiments, to help

us draw reliable insights from data.

● To be able understand business use-cases and use various

sources to collect and annotate datasets for the business problems.

● To have a strong academic background with good analytical

skill and exposure to machine learning and information retrieval

domain and technologies

● Strong programming skills, must be able to work in

programming languages such as Python, C/C++, etc..

● Acquire data from primary or secondary data sources and

perform data tagging

● Filter and clean data as per the business requirement and

maintain a well-defined, structured and clean database

● Work on data labeling tool(s) and annotate data for machine

learning models. Sift through structured and unstructured data;

identify the right content and annotate with the right label

● Interpret data, analyse results using statistical techniques and

models and conduct exploratory analysis

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