Senior Analyst - Data Science

Posted 2 Days Ago
Be an Early Applicant
Hiring Remotely in Office, Machaze, Manica, MOZ
Remote
Senior level
Software • Financial Services
The Role
Develop and deploy machine learning and predictive analytics solutions across classification, forecasting, segmentation, attribution, and recommendation use cases. Analyze complex data, generate business insights, and present recommendations to stakeholders. Build AI and generative AI solutions, operationalize models through AWS SageMaker and MLOps practices, and collaborate with engineering and business teams. The role also involves mentoring junior colleagues, leading analytical workstreams, and driving adoption of analytics capabilities.
Summary Generated by Built In
About the OpportunityJob Type: Permanent

Application Deadline: 17 November 2026

 

Job Description

                                                                                                

Title              Senior Analyst - Data Science

Department      Analytics

Location          Gurgaon

Level                Data Scientist 4


We are proud to have been helping our clients build better financial futures for over 50 years. How have we achieved this? By working together and supporting each other across the globe. Join our Business Analytics team and become part of something bigger.

 

About Our Team


Fidelity's Business Analytics team supports Fidelity Canada by delivering advanced analytics, machine learning, reporting, and AI-driven solutions that help business leaders make informed decisions. The team partners closely with stakeholders across Sales, Marketing, Client Services, Products, and Operations to uncover insights, optimize performance, improve client experiences, and drive strategic growth. By combining business expertise with innovative analytics capabilities, the team enables data-driven decision-making across the organization.

 

About the Role

 

Are you passionate about solving complex business problems through data science and machine learning? Do you enjoy transforming data into actionable insights and building solutions that create measurable business impact? If so, we have an exciting opportunity for you.

We are looking for a Senior Analyst - Data Science to join our Business Analytics team and contribute to the following areas:

 

Machine Learning & Predictive Analytics

  • Design, develop, validate, and deploy machine learning models to address key business challenges.
  • Build solutions across classification, forecasting, segmentation, propensity, attribution, and recommendation use cases.
  • Evaluate model performance and continuously improve solution effectiveness.

Advanced Analytics & Insight Generation

  • Analyze large and complex datasets to identify trends, opportunities, and actionable business insights.
  • Translate analytical findings into recommendations that influence strategic and operational decisions.
  • Present analytical results to business stakeholders in a clear and compelling manner.

AI & Generative AI Solutions

  • Explore and implement emerging AI and Generative AI technologies to enhance business processes and decision-making.
  • Identify opportunities to leverage AI-driven solutions that improve client experience and operational efficiency.
  • Support experimentation and innovation across the analytics ecosystem.

Cloud Analytics & MLOps

  • Develop and operationalize machine learning solutions using platforms such as AWS SageMaker, Snowflake, Salesforce, Adobe, and other enterprise technologies.
  • Follow MLOps best practices for model deployment, monitoring, governance, and scalability.
  • Partner with data engineering teams to improve data accessibility, automation, and solution performance.

Stakeholder Partnership & Delivery

  • Collaborate closely with business partners, technology teams, and data engineers to understand business requirements and translate them into scalable analytical solutions.
  • Manage multiple priorities while ensuring high-quality and timely delivery of projects.
  • Drive adoption of analytics solutions by demonstrating measurable business value.

Team Collaboration & Capability Building

  • Contribute to building analytics and AI capabilities across the team.
  • Share best practices, mentor junior team members, and support a culture of continuous learning and innovation.
  • Stay current with the latest developments in data science, machine learning, cloud analytics, and AI technologies.

 

 

 

About You


To be successful in this role, you should possess the following qualifications and experience:

 

Required Qualifications

 

  • Bachelor's or master’s degree in computer science, Engineering, Statistics, Mathematics, Economics, or a related quantitative discipline.
  • 5-8 years of experience in Data Science, Machine Learning, Advanced Analytics, or a related field, with a proven track record of delivering end-to-end analytical and machine learning solutions in a business environment.
  • Experience leading analytical workstreams, influencing stakeholders, and translating complex business problems into scalable data science solutions.
  • Strong proficiency in Python, SQL, and data manipulation techniques.
  • Hands-on experience developing and deploying machine learning models using frameworks such as Scikit-learn, TensorFlow, or PyTorch.
  • Experience developing and operationalizing machine learning solutions using AWS SageMaker and cloud-based analytics environments.
  • Strong understanding of predictive modelling, forecasting, attribution modelling, recommender systems, segmentation, and statistical techniques.
  • Experience working with structured and unstructured data to generate actionable business insights.
  • Excellent problem-solving, analytical thinking, and communication skills.
  • Ability to work effectively with business stakeholders, technology teams, and data engineers in a fast-paced environment.

 

Preferred Qualifications

 

  • Experience with Snowflake, Adobe Analytics, Salesforce, or similar enterprise data platforms.
  • Familiarity with MLOps concepts, model governance, deployment, and monitoring best practices.
  • Exposure to Generative AI, Large Language Models (LLMs), agentic AI frameworks, and emerging AI technologies.
  • Experience within financial services, wealth management, asset management, or related industries would be an advantage.
  • Degree from a leading engineering, mathematics, economics, analytics, or computer science program preferred.

 

Feel Rewarded


For starters, we'll offer you a comprehensive benefits package. We'll value your wellbeing and support your professional development. We'll also be as flexible as we can about where and when you work, finding a balance that works for all of us. It's all part of our commitment to helping you feel motivated by the work you do and proud to be part of our team.

For more about our work, our approach to dynamic working, and how you could build your future here, visit careers.fidelityinternational.com.

 

Skills Required

  • Bachelor's or master's degree in computer science, engineering, statistics, mathematics, economics, or a related quantitative discipline.
  • 5-8 years of experience in data science, machine learning, advanced analytics, or a related field.
  • Experience delivering end-to-end analytical and machine learning solutions in a business environment.
  • Experience leading analytical workstreams and influencing stakeholders.
  • Strong proficiency in Python, SQL, and data manipulation techniques.
  • Hands-on experience developing and deploying machine learning models using Scikit-learn, TensorFlow, or PyTorch.
  • Experience developing and operationalizing machine learning solutions using AWS SageMaker and cloud-based analytics environments.
  • Strong understanding of predictive modeling, forecasting, attribution modeling, recommender systems, segmentation, and statistical techniques.
  • Experience working with structured and unstructured data to generate actionable business insights.
  • Excellent problem-solving, analytical thinking, and communication skills.
  • Ability to work effectively with business stakeholders, technology teams, and data engineers in a fast-paced environment.
  • Experience with Snowflake, Adobe Analytics, Salesforce, or similar enterprise data platforms.
  • Familiarity with MLOps concepts, model governance, deployment, and monitoring best practices.
  • Exposure to generative AI, large language models, agentic AI frameworks, and emerging AI technologies.
  • Experience within financial services, wealth management, asset management, or related industries.
  • Degree from a leading engineering, mathematics, economics, analytics, or computer science program.

Fidelity International Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Fidelity International and has not been reviewed or approved by Fidelity International.

  • Parental & Family Support — Equalised paid parental leave and five paid days for caring responsibilities are explicitly provided. Feedback suggests these policies are a notable strength for employees with family needs.
  • Wellbeing & Lifestyle Benefits — Mental-health support, an Employee Assistance Programme, and trained Mental Health First Aiders are part of the offering. Broader physical, mental, and financial-wellbeing resources are highlighted alongside healthcare support.
  • Flexible Benefits — Many roles follow a hybrid model that allows working from home with minimum office attendance. Feedback suggests this flexibility supports work-life balance in practice.

Fidelity International Insights

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The Company
HQ: London
9,919 Employees
Year Founded: 1969

What We Do

Fidelity International offers investment solutions and services and retirement expertise to more than 2.5 million customers globally. As a privately held, purpose-driven company with a 50-year heritage, we think generationally and invest for the long term. Operating in more than 25 countries and with $739.9 billion* in total assets, our clients range from central banks, sovereign wealth funds, large corporates, financial institutions, insurers and wealth managers, to private individuals. Our Workplace & Personal Financial Health business provides individuals, advisers and employers with access to world-class investment choices, third-party solutions, administration services and pension guidance. Together with our Investment Solutions & Services business, we invest $567 billion on behalf of our clients. By combining our asset management expertise with our solutions for workplace and personal investing, we work together to build better financial futures. *Data as of 31 March 2021

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