Junior Data Scientist / ML developer

We are looking for a talented Data Scientist to join our team. The ideal candidate will have a strong foundation in data analysis, statistical models, and machine learning algorithms. You will work closely with the team to solve complex problems and drive business decisions using data. This role requires strategic thinking, problem-solving skills, and a passion for data.

Responsibilities
1. Analyse large, complex datasets to extract insights and determine appropriate techniques to use.
2. Build predictive models, machine learning algorithms and conduct A/B tests to assess the effectiveness of models.
3. Present information using data visualization techniques.
4. Collaborate with different teams (e.g., product development, marketing) and stakeholders to understand business needs and devise possible solutions.
5. Stay updated with the latest technology trends in data science.
6. Develop and implement real-time machine learning models for various projects.
7. Engage with clients and consultants to gather and understand project requirements and expectations.
8. Write well-structured, detailed, and compute-efficient code in Python to facilitate data analysis and model development.
9. Utilize IDEs such as Jupyter Notebook, Spyder, and PyCharm for coding and model development.
10. Apply agile methodology in project execution, participating in sprints, stand-ups, and retrospectives to enhance team collaboration and efficiency.
11. Engage stakeholders to present findings and insights.
Skill Requirements
1. Proficiency in scripting languages like Python and R.
2. Experience with SQL and familiarity with databases like Snowflake and Oracle.
3. Experience with data visualization tools like Tableau or PowerBI.
4. Solid understanding of mathematics, statistics, algorithms, and hands-on experience with machine learning/statistical techniques, including regression, classification, and ensemble methods.
5. Excellent problem-solving skills and the ability to manage multiple tasks.
6. Familiarity with cloud services like AWS, Google Cloud, and Azure.
7. Proficiency in relational data modeling.
8. Familiarity with version control systems like Git.
9. Proficiency in MS Excel.
10. Knowledge of machine learning frameworks like TensorFlow and PyTorch.
11. Exposure to big data platforms like Hadoop and Spark.
12. Strong communication skills to effectively collaborate with teams and explain complex results to non-technical stakeholders.
13. Detail-oriented mindset with a passion for accuracy.
14. Experience in training, fine-tuning, and deploying open-source LLMs.
15. Familiarity with LangChain, RAG, and Vector DBs.
16. Familiarity with LLM models like GPT-4, BERT, etc.
17. Experience with DataRobot, Azure ML Studio, or other automated machine learning platforms.

1. Bachelors degree in computer science, Mathematics, Statistics, or a related field.
2. 1-2 years of experience in data analysis or data science-related field.
3. Overall experience of 3-5 years in data science or a related field.