6+ NumPy Jobs in Pune | NumPy Job openings in Pune

Department

Product & Technology

Location

On-site | Prabhat Road, Pune

Experience

3-5 Years in a Data Engineering or Analytics Role

Domain

Fintech / Wealth Management — non-negotiable

Compensation

11-12 LPA Fixed + Performance Bonus

Growth

Title upgrade + salary revision at 12–18 months for strong performers

Why this role is different from most Data Engineer postings

You will work directly with the founding team on a live wealth management platform used by HNI and NRI clients. You will not spend years in a queue waiting to matter your work ships to production, your analysis influences product decisions, and you will guide junior teammates from day one. If you perform, a raise and title upgrade are on the table within 1218 months. This is the kind of early-team role that defines careers.

About Cambridge Wealth

Cambridge Wealth is a fast-growing, award-winning Financial Services and Fintech firm obsessed with quality and exceptional client service. We serve a high-profile clientele NRI, Mass Affluent, HNI, and ultra-HNI professionals and have received multiple awards from major Mutual Fund houses and BSE. We are past the zero-to-one stage and now focused on scaling our features and intelligence layer. You will be joining at exactly the right time.

What You Will Be Doing

This is a central, hands-on data engineering role at the intersection of financial analytics and applied ML. You will own the data pipelines and analytical models that power investment insights for wealth management clients transforming transaction data and portfolio information into measurable, actionable intelligence.

We are not looking for someone who just keeps the lights on. We want someone who looks at a working system and immediately sees how to make it 10x faster, cleaner, and smarter using AI and automation wherever possible.

Key Responsibilities:

Data Engineering & Pipelines

• Build and optimize PostgreSQL-based pipelines to process large volumes of investment transaction data.
• Design and maintain database schemas, foreign tables, and analytical structures for performance at scale.
• Write advanced SQL — window functions, stored procedures, query optimization, index design.
• Build Python automation scripts for data ingestion, transformation, and scheduled pipeline runs.
• Monitor AWS RDS workloads and troubleshoot performance issues proactively.

Financial Analytics & Modelling

• Develop analytical frameworks to evaluate client portfolios against benchmarks and category averages.
• Build data models covering mutual fund schemes, SIPs, redemptions, switches, and transfer lifecycles.
• Create materialized views and derived tables optimized for dashboards and internal reporting tools.
• Analyse client transaction history to surface patterns in investment behaviour and financial discipline.

Applied ML & AI-Driven Development

• Use Python (Pandas, NumPy, Scikit-learn) for trend analysis, forecasting, and predictive modelling.
• Implement classification or regression models to support financial pattern detection.
• Use AI tools — LLMs, Copilots — to accelerate ETL development, code quality, and data cleaning.
• Identify opportunities to automate repetitive data tasks and advocate for smarter tooling.

Data Quality & Governance

• Own data integrity end-to-end in a live, high-stakes financial environment.
• Build and maintain validation and cleaning protocols across all financial datasets.
• Maintain Excel models, Power Query workflows, and structured reporting outputs.

Collaboration & Junior Mentorship

• Work directly with Product, Investment Research, and Wealth Advisory teams.
• Translate open-ended business questions into structured queries and measurable outputs.
• Guide 1–2 junior trainees — review their work, set code quality standards, and help them grow.
• Present findings clearly to non-technical stakeholders — no jargon, just clarity.

Skills — What We Need vs. What Helps

Skill / Tool

Requirement

Must-Haves:

SQL & PostgreSQL (window functions, stored procedures, optimization)

Python — Pandas, NumPy for data processing and automation

ML fundamentals — classification or regression (Scikit-learn)

AWS RDS or equivalent cloud database experience

Financial domain knowledge — mutual funds, SIPs, portfolio concepts

Python data visualization — Matplotlib, Seaborn, or Plotly

Strong Advantage

Excel — Power Query, advanced modelling

Materialized views, query planning, index optimization

Experience with BI/dashboard tools

Good to Have

NoSQL databases

Prior fintech or wealth management startup experience

Financial Domain — Non-Negotiable

This is a wealth management platform. You must come in with a working understanding of:

• Mutual fund structures, scheme types, and NAV-based transactions
• Investment lifecycle — SIPs, Lump Sum, Redemptions, Switches, and STPs
• Portfolio allocation and benchmarking against indices (e.g. Nifty 50, category averages)
• How HNI/NRI clients interact with financial products differently from retail investors

You do not need to be a CFA. But if mutual funds and portfolio analytics are completely new territory, this role is not the right fit right now.

The Culture Fit — Read This Carefully

We are a small, fast-moving team. This is not a place where you wait for a ticket to arrive in your queue. The right person for this role:

• Has worked at a small startup before and is used to wearing multiple hats
• Finds broken or slow data systems genuinely irritating and fixes them without being asked
• Reaches for Python or an LLM when there is a repetitive task — automating is instinctive
• Is comfortable saying 'I don't know but I'll find out' and follows through independently
• Wants visibility and ownership, not just a well-defined job description
• Is looking for a role where strong performance is directly visible and rewarded

Growth Path — What Happens If You Perform

This is not a vague 'growth opportunity' pitch.

If you hit the bar in your first 12–18 months, you will receive a salary revision and a title upgrade to Senior Data Engineer or Lead Data Engineer depending on team expansion. As we scale our Data and AI team, this role is the natural stepping stone to a team lead position. You will also gain direct exposure to founding-team decision-making — the kind of access that is hard to get at larger companies.

Preferred Background

• 2–4 years in a data engineering or analytics role at a startup or small Fintech
• Experience in a live product environment where data errors have real consequences
• Exposure to portfolio analytics, investment research, or wealth management platforms
• Has mentored or reviewed code for at least one junior team member

Hiring Process

We respect your time. The process is direct and moves fast.

• Screening Questions — 5 minutes online
• Online Challenge — MCQ(Data, SQL, AWS, etc), and one applied ML or analytics problem, Communication Skills and Personality (focused, not trick questions)
• People Round — 30-minute video call, culture and communication
• Technical Deep-Dive — 1 hour in person, live financial data problems and your past work
• Founder's Interview — 1 hour in person, growth conversation and mutual fit
• Offer & Background Verification

Specific Knowledge/Skills

1. 4-6 years of experience
2. Proficiency in Python programming.
3. Basic knowledge of front-end development.
4. Basic knowledge of Data manipulation and analysis libraries
5. Code versioning and collaboration. (Git)
6. Knowledge for Libraries for extracting data from websites.
7. Knowledge of SQL and NoSQL databases
8. Familiarity with RESTful APIs
9. Familiarity with Cloud (Azure /AWS) technologies

JioTesseract, a digital arm of Reliance Industries, is India's leading and largest AR/VR organization with the mission to democratize mixed reality for India and the world. We make products at the cross of hardware, software, content and services with focus on making India the leader in spatial computing. We specialize in creating solutions in AR, VR and AI, with some of our notable products such as JioGlass, JioDive, 360 Streaming, Metaverse, AR/VR headsets for consumers and enterprise space.

Mon-Fri, In office role with excellent perks and benefits!

Key Responsibilities:

1. Design, develop, and maintain backend services and APIs using Node.js or Python, or Java.

2. Build and implement scalable and robust microservices and integrate API gateways.

3. Develop and optimize NoSQL database structures and queries (e.g., MongoDB, DynamoDB).

4. Implement real-time data pipelines using Kafka.

5. Collaborate with front-end developers to ensure seamless integration of backend services.

6. Write clean, reusable, and efficient code following best practices, including design patterns.

7. Troubleshoot, debug, and enhance existing systems for improved performance.

Mandatory Skills:

1. Proficiency in at least one backend technology: Node.js or Python, or Java.

2. Strong experience in:

i. Microservices architecture,

ii. API gateways,

iii. NoSQL databases (e.g., MongoDB, DynamoDB),

iv. Kafka

v. Data structures (e.g., arrays, linked lists, trees).

3. Frameworks:

i. If Java : Spring framework for backend development.

ii. If Python: FastAPI/Django frameworks for AI applications.

iii. If Node: Express.js for Node.js development.

Good to Have Skills:

1. Experience with Kubernetes for container orchestration.

2. Familiarity with in-memory databases like Redis or Memcached.

3. Frontend skills: Basic knowledge of HTML, CSS, JavaScript, or frameworks like React.js.

Who are we looking for?  

We are looking for a Senior Data Scientist, who will design and develop data-driven solutions using state-of-the-art methods. You should be someone with strong and proven experience in working on data-driven solutions. If you feel you’re enthusiastic about transforming business requirements into insightful data-driven solutions, you are welcome to join our fast-growing team to unlock your best potential.  

Job Summary 

• Supporting company mission by understanding complex business problems through data-driven solutions. 
• Designing and developing machine learning pipelines in Python and deploying them in AWS/GCP, ... 
• Developing end-to-end ML production-ready solutions and visualizations. 
• Analyse large sets of time-series industrial data from various sources, such as production systems, sensors, and databases to draw actionable insights and present them via custom dashboards. 
• Communicating complex technical concepts and findings to non-technical stakeholders of the projects 
• Implementing the prototypes using suitable statistical tools and artificial intelligence algorithms. 
• Preparing high-quality research papers and participating in conferences to present and report experimental results and research findings. 
• Carrying out research collaborating with internal and external teams and facilitating review of ML systems for innovative ideas to prototype new models. 

Qualification and experience 

• B.Tech/Masters/Ph.D. in computer science, electrical engineering, mathematics, data science, and related fields. 
• 5+ years of professional experience in the field of machine learning, and data science. 
• Experience with large-scale Time-series data-based production code development is a plus. 

Skills and competencies 

• Familiarity with Docker, and ML Libraries like PyTorch, sklearn, pandas, SQL, and Git is a must. 
• Ability to work on multiple projects. Must have strong design and implementation skills. 
• Ability to conduct research based on complex business problems. 
• Strong presentation skills and the ability to collaborate in a multi-disciplinary team. 
• Must have programming experience in Python. 
• Excellent English communication skills, both written and verbal. 

Benefits and Perks

• Culture of innovation, creativity, learning, and even failure, we believe in bringing out the best in you. 
• Progressive leave policy for effective work-life balance. 
• Get mentored by highly qualified internal resource groups and opportunity to avail industry-driven mentorship program, as we believe in empowering people.  
• Multicultural peer groups and supportive workplace policies.  
• Work from beaches, hills, mountains, and many more with the yearly workcation program; we believe in mixing elements of vacation and work. 

 Hiring Process 

• Call with Talent Acquisition Team: After application screening, a first-level screening with the talent acquisition team to understand the candidate's goals and alignment with the job requirements. 
• First Round: Technical round 1 to gauge your domain knowledge and functional expertise. 
• Second Round: In-depth technical round and discussion about the departmental goals, your role, and expectations.
• Final HR Round: Culture fit round and compensation discussions.
• Offer: Congratulations you made it!  

If this position sparked your interest, apply now to initiate the screening process.

Key skills : Python, Numpy, Panda, SQL, ETL 

Roles and Responsibilities:

- The work will involve the development of workflows triggered by events from other systems

- Design, develop, test, and deliver software solutions in the FX Derivatives group

- Analyse requirements for the solutions they deliver, to ensure that they provide the right solution

- Develop easy to use documentation for the frameworks and tools developed for adaption by other teams

Familiarity with event-driven programming in Python

- Must have unit testing and debugging skills

- Good problem solving and analytical skills

- Python packages such as NumPy, Scikit learn

- Testing and debugging applications.

- Developing back-end components.

• Partners with business stakeholders to translate business objectives into clearly defined analytical projects.
• Identify opportunities for text analytics and NLP to enhance the core product platform, select the best machine learning techniques for the specific business problem and then build the models that solve the problem.
• Own the end-end process, from recognizing the problem to implementing the solution.
• Define the variables and their inter-relationships and extract the data from our data repositories, leveraging infrastructure including Cloud computing solutions and relational database environments.
• Build predictive models that are accurate and robust and that help our customers to utilize the core platform to the maximum extent.

• 12 to 15 yrs of experience.
• An advanced degree in predictive analytics, machine learning, artificial intelligence; or a degree in programming and significant experience with text analytics/NLP. He shall have a strong background in machine learning (unsupervised and supervised techniques). In particular, excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, logistic regression, MLPs, RNNs, etc.
• Experience with text mining, parsing, and classification using state-of-the-art techniques.
• Experience with information retrieval, Natural Language Processing, Natural Language
• Understanding and Neural Language Modeling.
• Ability to evaluate the quality of ML models and to define the right performance metrics for models in accordance with the requirements of the core platform.
• Experience in the Python data science ecosystem: Pandas, NumPy, SciPy, sci-kit-learn, NLTK, Gensim, etc.
• Excellent verbal and written communication skills, particularly possessing the ability to share technical results and recommendations to both technical and non-technical audiences.
• Ability to perform high-level work both independently and collaboratively as a project member or leader on multiple projects.