ACL Digital | Data Scientist
6 days ago
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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