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
  ,
  Randomized SearchCV
  ).

• 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
  bachelor's or master's degree in computer science
  ,
  statistics
  ,
  mathematics
  , or a related field.
• 3-5 years 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.