Junior Data Scientist

We are seeking a motivated and results-driven Junior Data Scientist with a passion for problem-solving, data analytics, and natural language processing (NLP). In this role, you will leverage your skills in Python, SQL, Machine learning, and NLP to develop data-driven solutions that drive business decisions and insights. You will be part of a dynamic team and work closely with senior data scientists and business stakeholders to create and optimize models, perform data analysis, and automate processes.

As a Junior Data Scientist, you will have the opportunity to work on a variety of projects, ranging from predictive modelling to text analysis and cloud-based data solutions. You should have a solid foundation in logical thinking, problem-solving, and the ability to apply your knowledge to real-world challenges.

Roles & Responsibilities

• Work independently to manage multiple projects at once while ensuring deadlines are met and data output is accurate and appropriate for the business.
• Implementation of newer algorithms according to the business needs.
• Collaborate with cross functional agile teams of software engineers, product managers, and others in building new product features.
• Think strategically about data as a core enterprise asset and assist in all phases of the advanced analytic development process.

Key Technical Skills:

• Programming

  :
• Strong proficiency in

  Python

  , with experience in libraries like

  pandas

  ,

  numpy

  ,

  scikit-learn

  ,

  networkx

  , and

  TensorFlow

  for data manipulation and machine learning tasks.
• Proficient in building and deploying high-performance APIs using

  FastAPI

  and

  Python

  , ensuring fast response times and scalability.
• Familiarity with Linux/Unix/Shell environments.
• Experience with Data Structures and Algorithms.

• Machine Learning

  :
• Hands-on experience with

  supervised learning

  (e.g.,regression, classification),

  unsupervised learning

  (e.g., clustering, PCA), and

  ensemble methods

  (e.g., random forests,gradient boosting).
• Familiarity with model evaluation metrics (e.g.,

  accuracy

  ,

  precision

  ,

  recall

  ,

  F1-score

  ,

  ROC-AUC

  ) and techniques for hyperparameter tuning (e.g.,

  GridSearchCV

  ,

  RandomizedSearchCV

  ).

• Natural Language Processing (NLP)

  :
• Understanding of key NLP tasks like text classification, sentiment analysis, named entity recognition (NER), and text summarization using traditional techniques (e.g., TF-IDF, bag-of-words) and pre-trained models.
• Experience with using LLMs such as

  GPT

  ,

  BERT

  , and

  T5

  for text generation, question answering, and document classification, using libraries like

  Hugging Face Transformers

  .
• Ability to fine-tune pre-trained LLMs on domain-specific data and evaluate model performance using metrics like accuracy, F1-score, bleu score, and perplexity, optimizing models for production use.

• SQL & Database Management

  :
• Strong SQL skills for querying relational databases (e.g.,

  PostgreSQL

  ,

  MySQL

  ) and managing large datasets.
• Experience in writing complex queries for data extraction, transformation, and aggregation.

• Azure Cloud Services

  :
• Familiarity with

  Azure Databricks

  ,

  Azure Blob Storage

  , and

  Azure SQL Database

  for data processing and storage.
• Basic knowledge of

  Azure Data Factory

  for building and orchestrating data pipelines.

• Data Visualization

  :
• Experience creating visualizations with

  matplotlib

  ,

  seaborn

  , and

  plotly

  for data exploration and model results presentation.
• Familiarity with dashboarding tools like

  Power BI

  or

  Tableau

  (optional).

• Git

• Proficient in creating and managing feature branches, resolving merge conflicts, and merging code into the main branch using

  Git merge

  and

  Git rebase

  .
• Experienced with

  pull requests (PRs)

  , reviewing and commenting on code, and working within

  Git workflows

  (e.g.,

  GitFlow

  or feature branching) to ensure smooth team collaboration.

Required Qualifications:

• A

  bachelors or masters degree in computer science

  ,

  statistics

  ,

  mathematics

  , or a related field.
• 12-18 Months of professional experience as a

  Data Scientist

  , working with machine learning, data analysis, NLP, and cloud technologies.
• Strong communication skills, with the ability to explain complex data science concepts to non-technical stakeholders.
• Ability to work independently and as part of a team in a fast-paced environment.

Nice-to-Have Skills:

• Experience with

  model deployment

  and

  CI/CD

  pipelines.
• Familiarity with

  big data technologies

  such as

  Spark

  or

  Hadoop

  .
• Experience with

  Docker

  for containerization and

  Kubernetes

  for model orchestration.