Data Analyst

Job Description:

As a Senior Data Scientist at Forbes Marshall, you will leverage your expertise in data analysis, machine learning, and statistical modeling to drive data-driven projects and solve complex business problems. You will collaborate with domain experts and cross-functional teams to develop and implement innovative solutions, ensuring the meaningful data insights to stakeholders and also to customers.

Key Responsibilities:
1. Data Analysis & Interpretation:

• Analyze large and complex datasets to identify trends, patterns, and insights.
  
• Translate data insights into actionable recommendations for business stakeholders/customers

2. Model Development & Implementation:

• Develop, test, and deploy predictive models and machine learning algorithms based on the application demand.
  
• Ensure models are robust, scalable, and meet business requirements.

3. Collaboration & Communication:

• Work closely with product experts, engineers, and other stakeholders to understand business needs and translate them into data solutions.
  
• Present findings and recommendations to both technical and non-technical audiences.

4. Research & Innovation:

• Stay updated with the latest advancements in data science, machine learning, LLM and AI.
  
• Identify and explore new technologies, tools, and methodologies to improve data science practices within the organization.

5. Mentorship & Leadership:

• Provide guidance and mentorship to junior data scientists and analysts.
  
• Lead and manage data science projects, ensuring timely delivery of the same.
  

Qualifications:
Education: BE / Masters in Data Science, Computer Science, Statistics, or Mathematics etc
Experience: 4-5 years of experience in data science or a related field, with a proven track record of delivering impactful data solutions.

Technical Skills:

• Proficiency in programming languages such as Python or R.
  
• Experience with cloud platform GCP,AWS etc
  
• Strong experience with data manipulation and analysis tools (e.g., SQL, Pandas, NumPy).
  
• Expertise in machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch).
  
• Familiarity with big data technologies.
  
• Should be familiar with deployment strategies, docker, kubernetes etc.
  

Analytical Skills: Excellent problem-solving skills with the ability to analyze complex data and provide insights.
Communication Skills: Strong written and verbal communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
Leadership: Demonstrated ability to lead projects and mentor team members.