Lead/Senior Data Scientist at DVT

Job description

• DVT is looking for a Lead Data Scientist to assist on a complex and intricate project in the renewable energy sector.

Job Requirements

Education & Experience:

• 8+ years of experience working on Data Science projects and ideally having led some of them.
• Bachelor’s, Master's or PhD in Computer Science, Statistics, Mathematics, or a related field. A Master’s degree is preferred.
• Certifications in data science, machine learning, or related fields are a plus.

Strong knowledge and extensive experience in:

• Knowledge of tools such SQL, Sci-Kit lean, Pandas, Numpy, jupyter notebook
• Exceptional knowledge of Machine Learning techniques on both the supervised and unsupervised learning fronts.
• Exceptional knowledge of time series forecasting.
• Track record and demonstratable knowledge of using the above algorithms to solve problems at client or at their employer.
• Well versed and good understanding on MLOps best practices and has been a part of a team that has taken models to prod, ideally at scale.
• Knowledgeable of MLOps tools like MLFlow, DVC, Airflow or cloud MLOps environments like Sagemaker, Azure ML studio of GCP’s vertex AI (Nice to have if they have practical experience)
• Databricks experience is advantageous

Roles and Responsibilities:

• Work independently on complex projects.
• Design and implement complex predictive models or algorithms to drive business growth and improve customer experiences
• Identify patterns and trends in data to drive insights and recommendations for business decisions
• Design experiments and A/B testing to validate hypotheses and assess impact of data-driven solutions
• Mentor and provide guidance to junior and intermediate data scientists.
• Be involved in project management and strategic decision-making
• Be involved in data pipeline architecture design and implementation Collaborate with cross-functional teams to gather requirements, design solutions, and implement models
• Communicate findings and recommendations to non-technical stakeholders in a clear and concise manner

Behaviour Competency:

• Self-motivated, proactive and results-oriented
• Strong analytical and problem-solving skills
• Ability to work in a fast-paced, dynamic and collaborative environment
• Comfortable with ambiguity and able to adapt to change
• Ability to work independently and as part of a team
• Passion for learning new technologies and staying up to date with the latest trends in data science and machine learning
• Excellent written and verbal communication and collaboration skills
• Shows promising leadership abilities
• Strong business acumen

Interview Process

• Recruiter call
• Online Assessment / Take Home assessment
• Technical Interview
• Decision & Feedback