At a Glance
- Tasks: Join a dynamic team to build innovative data solutions and enhance investment decision-making.
- Company: Be part of J.P. Morgan, a global leader in financial services.
- Benefits: Competitive salary, professional development, and the chance to work with cutting-edge technology.
- Why this job: Make a real impact in finance by leveraging your data science skills.
- Qualifications: Masters or PhD in a quantitative field with strong analytical and technical skills.
- Other info: Collaborate globally and enjoy excellent career growth opportunities.
The predicted salary is between 43200 - 72000 £ per year.
As a Data Scientist Senior Associate in the J.P. Morgan Asset Management Data Science Team (JPMAM), you will work closely with investment and data science professionals across Asset Management to proactively source, due diligence and draw insights from in-house investment and alternative data. This is an exciting opportunity to join a small, dynamic team with the resources and impact of one of the world's largest companies. We are looking for problem-solvers with a passion for building greenfield analytic solutions and helping to scale them for greater impact. The successful candidate will be expected to work on projects along the full data science spectrum, from data acquisition and wrangling, to model selection to presentation and data visualization. The role requires the successful candidate to work as part of a globally distributed data science team. They will work with stakeholders and subject matter experts to understand problems then find innovative, practical solutions. The successful candidate will be able to evidence a history of delivery and innovation.
Responsibilities
- Building tools and systems to understand decision data, context and events around it to enhance JPMAM's decision attribution capabilities and systematically identify opportunities.
- Working with portfolio managers to understand sources of alpha and opportunities to improve decision-making process.
- Working with partners in technology and user experience to build out tools providing real-time insights to portfolio managers and their teams.
Qualifications
- Masters Degree or PhD, in computer science, statistics, or other quantitative field.
- Strong analytical/modelling skills and business orientation with proven ability to use data and analytics to drive business results; strong technical background.
- Demonstrated experience working within a data science team.
- Timeseries analysis and modelling.
- Training and fine-tuning of the ML model for investment models.
- Strong knowledge of Python for data scientists (e.g., pandas), traditional ML and deep learning libraries (e.g., scikit learn, xgboost, TensorFlow, Torch, etc.).
- Data manipulation languages (e.g., SQL).
- Data visualization / presentation skills (e.g., Tableau).
- Demonstrated experience working with engineering, developers and other technology teams.
- Writing production quality code, unit testing and familiarity with version control.
- Familiarity with cloud-based technologies.
- Demonstrated experience using alternative datasets in investing and alpha research.
- In-depth understanding of financial markets required.
- Strong communications skills and the ability to present findings to a non-technical audience.
- Passion for learning and adopting a wide range of techniques in an agile environment.
- Prior experience working in alpha capture, performance attribution or trading / decision analytics role.
- Front office experience in finance (preferably buyside).
- Familiarity in incorporating unstructured data into investment research.
- Knowledge of alternative data landscape.
- CFA.
About JPMorgan
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. J.P. Morgan Asset & Wealth Management delivers industry-leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.
Data Science & Marchine Learning - Senior Associate - Asset Management in City of Westminster employer: Jpmorgan Chase & Co.
Contact Detail:
Jpmorgan Chase & Co. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science & Marchine Learning - Senior Associate - Asset Management in City of Westminster
✨Tip Number 1
Network like a pro! Reach out to current employees at J.P. Morgan or in the asset management field on LinkedIn. Ask them about their experiences and any tips they might have for landing a role like this. Personal connections can make all the difference!
✨Tip Number 2
Prepare for those interviews by brushing up on your technical skills. Make sure you can confidently discuss your experience with Python, machine learning models, and data visualisation tools. We want to see you shine when it comes to showcasing your analytical prowess!
✨Tip Number 3
Don’t forget to tailor your approach! When you get the chance to speak with interviewers, highlight your problem-solving skills and how you've used data to drive business results in past roles. Show them you’re not just a data whiz, but also a strategic thinker.
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of the J.P. Morgan team. Let’s get you that dream job!
We think you need these skills to ace Data Science & Marchine Learning - Senior Associate - Asset Management in City of Westminster
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your data science projects, especially those involving Python, machine learning, and data visualisation, as these are key for this role.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how your background aligns with our needs. Share specific examples of your problem-solving skills and any innovative solutions you've implemented in past roles.
Showcase Your Technical Skills: Don’t shy away from listing your technical proficiencies! Mention your experience with tools like SQL, TensorFlow, and any cloud technologies. We want to see how you can contribute to our data-driven decision-making process.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows your enthusiasm for joining our team!
How to prepare for a job interview at Jpmorgan Chase & Co.
✨Know Your Data Science Stuff
Make sure you brush up on your data science skills, especially in Python and machine learning libraries like scikit-learn and TensorFlow. Be ready to discuss your past projects and how you've used these tools to solve real-world problems.
✨Understand the Financial Landscape
Even if you come from a non-financial background, it's crucial to have a solid grasp of financial markets and investment strategies. Familiarise yourself with concepts like alpha capture and performance attribution, as this will help you connect your data skills to the role.
✨Prepare for Technical Questions
Expect technical questions that test your analytical and modelling skills. Practice explaining your thought process clearly and concisely, as you'll need to communicate complex ideas to non-technical stakeholders.
✨Show Your Passion for Learning
Demonstrate your enthusiasm for continuous learning and adapting to new techniques. Share examples of how you've kept up with industry trends or learned new technologies, as this shows you're proactive and committed to growth.