Data Scientist

Company Description

NeosAlpha, founded in the UK in 2017, specializes in IT consulting and digital transformation services for clients in the UK, USA, Australia, and Europe. We provide solutions in areas like intelligent automation, AI-driven integrations, cloud services, and data engineering. Our consultative approach ensures tailored, cost-effective solutions to modernize and transform digital ecosystems. Recognized with Boomi Partner Awards for three consecutive years, NeosAlpha excels in delivering seamless cloud integration and innovative strategies.

We are looking for a highly skilled Data Scientist to join our software services team. The ideal candidate will have

a strong foundation in analytics, machine learning, and cloud-based deployment, along with the ability to

collaborate with clients and cross-functional teams to deliver impactful data-driven solutions.

Designation:

Experience:

Location:

Education:

Key Responsibilities:

• Machine Learning Development: Design, build, and optimize classical ML models (regression, SVM,

decision trees, random forests, gradient boosting, clustering, dimensionality reduction).

• Python Programming: Write clean, efficient, and scalable Python code, leveraging libraries such as

NumPy, Pandas, Scikit-learn, etc.

• Deep Learning Systems: Implement and fine-tune deep learning models (CNNs, RNNs, Transformers)

using frameworks like TensorFlow or PyTorch.

• Generative AI (Good Exposure Required): Work with LLMs, Transformers, GANs, VAEs; fine-tune and

optimize GenAI models; contribute to prompt engineering and applied use cases.

• Data Management & Feature Engineering: Handle large datasets, perform preprocessing, augmentation,

and feature engineering for ML workflows.

• Model Deployment & Monitoring: Deploy models into production and monitor performance, addressing

issues like drift, bias, or overfitting.

• Coding Standards: Participate in code reviews, ensure best practices in coding, scalability, and

maintainability of ML solutions.

• Build and automate data pipelines and workflows using tools such as Airflow, Spark, or Dataflow.

• Collaboration: Work closely with cross-functional teams including engineers and product managers to

integrate ML/GenAI solutions into real-world applications.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or related

fields.

• Primary Skills: Strong expertise in Machine Learning and Python programming.

• Good exposure to Generative AI (LLMs, Transformers, Prompt Engineering, Fine-tuning models).

• Experience with ML/DL frameworks such as TensorFlow, PyTorch, or Keras.

• Good mathematical/statistical foundation in probability, optimization, and modeling.

• Familiarity with deployment platforms (AWS Sage Maker, Azure ML, GCP AI) and MLOps practices are an

advantage.

• Strong coding discipline, with experience in writing optimized, production-ready code.

Soft Skills & Behavioral Competencies:

• Strong problem-solving and analytical mindset.

• Excellent communication and collaboration skills.

• Self-motivated, reliable, and detail-oriented.

• Ability to manage time effectively and meet deadlines.

• Eagerness to learn and adapt to emerging technologies.