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For Companies At a Glance
- Tasks: Dive into data to uncover patterns and drive product innovation.
- Company: Join a forward-thinking company focused on leveraging data for impactful solutions.
- Benefits: Enjoy a dynamic work environment with opportunities for growth and learning.
- Why this job: Be at the forefront of data science, shaping products that make a difference.
- Qualifications: 8+ years in data querying, scripting, and solving analytical problems required.
- Other info: This is a 12-month contract role with potential for future opportunities.
The predicted salary is between 43200 - 72000 £ per year.
Duration – 12 months
RESPONSIBILITIES
- Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.
- Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the data.
- Generate and test hypotheses and analyze and interpret the results of product experiments.
- Work with product engineers to translate prototypes into new products, services, and features and provide guidelines for large-scale implementation.
- Provide Business Intelligence (BI) and data visualization support, which includes, but limited to support for the online customer service dashboards and other ad-hoc requests requiring data analysis and visual support.
MUST HAVES
- 8+ years experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R)
- 8+ years of experience solving analytical problems using quantitative approaches, understanding ecosystems, user behaviors & long-term product trends, and leading data-driven projects from definition to execution (including defining metrics, experiment, design, communicating actionable insights)
Data Scientist employer: Morgan McKinley
Contact Detail:
Morgan McKinley Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Make sure to showcase your experience with data querying languages like SQL and scripting languages such as Python. Highlight specific projects where you've successfully applied these skills to solve analytical problems.
✨Tip Number 2
Demonstrate your ability to lead data-driven projects by discussing your role in defining metrics and designing experiments. Use concrete examples to illustrate how your insights have led to actionable outcomes.
✨Tip Number 3
Familiarize yourself with the latest trends in machine learning and data visualization. Being able to discuss current methodologies and tools will show that you are proactive and knowledgeable in your field.
✨Tip Number 4
Network with professionals in the data science community, especially those who work in product development. Engaging with others can provide valuable insights and potentially lead to referrals for the position.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your 8+ years of experience with data querying languages, scripting languages, and statistical software. Provide specific examples of how you've solved analytical problems and led data-driven projects.
Showcase Technical Skills: Clearly outline your proficiency in SQL, Python, R, and any other relevant tools or technologies. Mention specific projects where you applied these skills to achieve measurable results.
Demonstrate Analytical Thinking: In your application, illustrate your ability to recognize patterns and pose business questions. Share instances where your analytical approach led to valuable discoveries or product improvements.
Tailor Your Application: Customize your CV and cover letter to align with the responsibilities listed in the job description. Use keywords from the job posting to ensure your application resonates with the hiring team.
How to prepare for a job interview at Morgan McKinley
✨Showcase Your Technical Skills
Be prepared to discuss your experience with data querying languages like SQL and scripting languages such as Python. Highlight specific projects where you applied these skills to solve analytical problems.
✨Demonstrate Problem-Solving Abilities
Prepare examples of how you've tackled complex analytical challenges in the past. Discuss your approach to defining metrics, designing experiments, and deriving actionable insights from data.
✨Familiarize Yourself with Business Intelligence Tools
Since the role involves providing BI and data visualization support, make sure to mention any experience you have with relevant tools. Be ready to discuss how you've used data visualization to support decision-making.
✨Communicate Clearly and Effectively
During the interview, practice articulating your thoughts clearly. Explain your methodologies and findings in a way that is understandable to both technical and non-technical stakeholders.
