Data Scientist and Machine Learning Engineer

Develop and implement machine learning models and algorithms to solve complex business problems.

Manage data collection, cleaning, and preprocessing, along with feature engineering to ensure the data quality and readiness for machine learning tasks.

Build and deploy statistical models to analyze and interpret large datasets, identifying trends, patterns, and insights.

Conduct exploratory data analysis to gain insights into data characteristics, anomalies, and potential biases. Train, fine-tune, and optimize complex machine learning models using large datasets.

Develop data pipelines and workflows for efficient data processing, cleansing, and transformation.

Collaborate with cross-functional teams to gather requirements, define project objectives, and deliver solutions that meet business needs.

Work under the guidance of lead data scientist and follow best practices in data science, statistical modeling, and data engineering.

Stay abreast of the latest advancements in machine learning techniques, statistical methods, and data engineering technologies.

Communicate findings and recommendations to stakeholders through clear and concise presentations and reports.

Required Skills, Experience & Qualities:

• The ideal candidate will be a quick learner, well-versed in the latest AI/ML and data trends and have a track record of delivering successful outcomes.
• Bachelor's or Master's in Computer Science, Mathematics/Statistics, or related field.
• Proven hands-on experience in data science, machine learning, statistical modeling, and data engineering. Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
• In-depth understanding of statistical concepts and techniques, with experience in hypothesis testing, regression analysis, time series analysis, etc. Proven track record of developing and implementing complex machine learning algorithms and models.
• Skilled AI/ML Engineer with expertise in NLP, Machine Learning, and Data Analytics. Proficiency in programming languages such as Python, R, or Java, with experience in libraries such as TensorFlow, PyTorch, scikit-learn, etc.
• Extensive experience with data preprocessing, Exploratory Data Analysis (EDA), feature engineering, and model evaluation. Comprehensive understanding of machine learning and deep learning algorithms. Specialization in Natural Language Processing, including areas such as Transformers, HuggingFace, etc.
• Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams.
• Proven track record of delivering high-quality solutions in a fast-paced environment.
• Ability to work independently and lead projects from inception to completion.