Data Scientist

Location : ,

Job Description

Job Title - Senior Data Scientist

Key responsibilities

• Lead end-to-end data science projects, from problem formulation and data collection to model deployment and result presentation.

• Collaborate with cross-functional teams to identify business challenges and opportunities that can be addressed using data analysis, machine learning and AI techniques.

• Design and implement innovative machine learning algorithms and models to solve complex business problems, such as predictive modeling, recommendation systems, and anomaly detection.

• Deliver technical solutions to evolve our trading platforms and solve business problems. This involves requirements gathering, identifying priorities, planning tasks and on-time delivery of solutions.

• Utilize and integrate LLMs (e.g., GPT, BERT) for natural language processing (NLP) tasks such as sentiment analysis, market news analysis, and automated report generation to enhance trading decisions.

• Explore, clean, and pre-process large datasets to extract relevant features and ensure data quality for analysis.

• Apply statistical analysis methods to uncover patterns, trends, and insights from data, and effectively communicate findings to both technical and non-technical stakeholders.

• Mentor and provide guidance to junior data scientists, helping them grow their technical and analytical skills.

• Stay up-to-date with the latest advancements in data science and machine learning techniques, and apply them to enhance our analytics capabilities.

• Collaborate with engineering teams to integrate data-driven solutions into production systems and ensure scalability and reliability.

• Participate in data-driven decision-making discussions with senior management and contribute to the overall data strategy of the company.

Skill and Experience

BS/MS in Engineering/Statistics/Computer Science/Economics or a related field

Experience working with energy and financial data, such as energy prices, supply and demand data, and economic indicators.

Knowledge of energy commodities trading, especially with North American Gas and Power Markets.

7-10+ years’ experience developing enterprise level ML, AI and LLM models and applications with cloud-based micro services such as AWS Lambda, S3, ECR, Sagemaker, etc.

Extensive experience with statistical modeling, machine learning algorithms (e.g., regression, classification, clustering), deep learning frameworks (e.g., TensorFlow, Keras, PyTorch), and NLP techniques (e.g., transformers, LSTM).

Proficiency in programming languages such as Python, with experience in using libraries like scikit-learn, pandas, NumPy, SciPy, Prophet and NLP libraries (e.g., Hugging Face Transformers, spaCy)

Advanced knowledge of Generalized Linear and Non-Linear Models, Time Series Analysis, Random Forest, Gradient Boosted Machines, Neural Networks.

Strong SQL proficiency and understanding of database technologies, such as AWS RDS and Snowflake/databricks.

Proficiency in data visualization tools (e.g., Tableau) to effectively communicate insights.

Solid understanding of statistical concepts and hypothesis testing. Experience working with large-scale datasets, databases, and data processing tools (e.g., SQL, Spark).

A portfolio showcasing previous data science projects and their business impact is highly desirable