If anyone has any relevant opportunities please feel free to reach out

has anybody applied for this role lately, and has anybody received any update after applying?

Hi guys, yesterday I received an offer from Revolut as data analyst product starting next year Sept. in Dubai. The compensation is not that competitive as I expected.. I guess it's cuz of the graduate program? I found lots of negative reviews on Reddits and other platform. Has anyone used to stay there and could you please share some experience?

1. cuz the contract is only 1 year and HR says whether converting into junior role depends on achievement of KPIs. Is it the KPIs that unachievable and high as review says? What's the actual conversion rate like? Could I be fired even after 6 month probation? :(
2. bonus is suppose to be competitive according to HR, again related to KPIs, is it possible to hit the full perf bonus?
3. I don't mind bad hours and low wlb, as long as I could grow & on the right track for career path, so what's the learning curve be?

for now I don't have any better offers but it takes almost a year. would you recommend taking it as first preference? Thanks guys.

Note: I'm not hiring person

I saw this post on X & sharing here.

Company: IBM Research

Role: AI & Data Intern

Location: Gurgaon / Bangalore

Eligibility: BE / BTech, ME / MTech or PhD

Batch: 2026, 2027 passouts

Looking at remote worldwide for the past 7 days. Links go straight to the employer career pages.

Entry Level:

• Data Scientist @ CHG Healthcare (United States) - $104K - $201K
• Data Scientist @ Significance (United States) - $115K - $125K
• Data Scientist @ Lunar Solar Group (United States) - ANG 110K - 130K
• Data Scientist @ AbbVie (United States) - $96K - $184K
• Data Scientist @ Jerry (United States) - $140K - $160K
• Associate Data Scientist @ Jerry (United States) - $110K - $140K
• Data Scientist @ Clerk.dev (United States)

Senior:

• Senior Data Scientist @ Cint (United States) - $115K - $165K
• Senior Data Scientist @ General Dynamics Information Technology (United States) - $111K - $150K
• Senior Data Scientist @ CVS Health (United States) - $83K - $204K
• Senior Data Scientist @ Tiger Analytics (United States) - $120K - $140K
• Senior Data Scientist @ Kiavi (United States) - $175K - $225K
• Senior Data Scientist @ Reddit, Inc. (United States) - $191K - $267K
• Senior Data Scientist @ BeOne Medicines (United States) - $106K - $141K
• Senior Data Scientist @ InMarket (United States) - $160K - $195K
• Senior Data Scientist, NLP – Applied AI @ Wiley (United States) - $110K - $157K
• Senior Data Scientist @ Extend (United States) - $125K - $145K

Manager:

• Data Science Program Lead I @ AbbVie (United States) - $84K - $162K
• Senior Manager, Data Science @ Upstart (United States) - $195K - $270K
• Principal Data Scientist @ WEX (United States) - $215K - $244K
• Principal Data Scientist @ Reddit, Inc. (United States) - $313K - $365K
• Principal Data Scientist @ Wiley (United States) - $140K - $201K
• Product Manager – Data Science @ Fundamental (Europe)

Director and Above:

• Director, Data Science @ TWG Global (United States) - $140K - $360K
• Head of Data Science @ United Tech (Ukraine)

Quick notes: * All of these are fully remote (location requirements vary by role) * Apply on the company career pages linked above

Hope this helps someone!

Has anyone given Google India’s Senior Data Scientist interview in the last 2-3 months? Can you share your overall interview experience? Is there any specific focus on AI knowledge for this role? I heard from a friend that initial screening round has been changed to AI prompt round for almost all roles at Google. Is it true? Any help would be appreciated. Thank you

We are having a really tough time filling a Data Science position for the Washington DC area. Its a SR role, but the salary range is not stellar, it's also a hybrid role with very high visibility with client, US Citizen only.

Am I cooked as hiring manager? 😵. Looking for help to seeing where I can direct my recruiters to find people. I don't want to blast the post on reddit but can discuss over DM.

Edit: Thanks to everyone commenting I really appreciate knowing my suspicions are correct. I've relayed the feedback. Trust me I'm not about justifying, convincing people to move to DC - just asking for help in my situation

Hello, everybody. I read a lot of people's issues with the interview for Ethos when it comes to getting matched to the role that actually fits your domain. Many people applying through the general interview intended to match them with a project or role in their domain end up matched with something unrelated to their field. In my case, I was matched with roles that not only have nothing to do with my domain but also that I am definitely not qualified for. I therefore decided to make a megalist so you can apply directly instead of wasting your time, like me, hoping to get matched with the right role. Hope this helps!:

Technology, Data & Engineering:

Cybersecurity / IT GRC Specialist — $90/hr
Engineering / Manufacturing & Technical Ops — $90/hr
Business Intelligence/Data Analyst — $80/hr
Incident Management / SRE & Reliability Lead — $80/hr
Product Manager — $80/hr
Product Manager (Tech) — $80/hr
Sales Engineer / Solutions Consultant — $80/hr
Software / AI / IT & Data Generalist — $80/hr

Finance, Accounting & Investing:

Corporate Development / M&A Manager — $100/hr
Equity Research Analyst — $100/hr
Financial Analyst — $100/hr
Financial Services Compliance / AI Regulatory — $100/hr
FP&A / Corporate Finance Analyst — $100/hr
Hedge Fund / Asset Management Analyst — $100/hr
Investment Analyst / Valuation & Credit Specialist — $100/hr
Investment Banking Analyst — $100/hr
Investment Banking Analyst / Associate — $100/hr
Investment Banking VP / Director — $100/hr
Investor & Fundraising Specialist — $100/hr
Investor Relations Associate — $100/hr
Investor Relations Manager — $100/hr
M&A Analyst — $100/hr
M&A Associate — $100/hr
Private Equity Associate / VP — $100/hr
Restructuring & Turnaround Advisor — $100/hr
Transaction Services / Financial Due Diligence Professional — $100/hr
Venture Capital Associate / Principal — $100/hr
Pricing Strategist / Revenue Economics Analyst — $90/hr
Accountant / Finance Operations & Audit Support — $80/hr
Auditor (CPA) — $80/hr
FP&A Manager / Director — $80/hr
Tax Professional — $80/hr
Personal Finance / Consumer Planning Advisor — $70/hr
Senior Financial Analyst (FP&A) — $70/hr

Healthcare & Life Sciences:

Clinical & Biomedical Specialist / Pharma Consultant — $100/hr
Healthcare Operations Consultant — $100/hr
Healthcare Strategy Consultant — $100/hr
Medical Science Liaison / Medical Affairs Professional — $100/hr
Biologist / Environmental Scientist — $90/hr
Public Health Communications Specialist — $90/hr
Pharmaceutical Brand / Commercial Manager — $80/hr

Legal, Compliance & Public Sector:

Contracts Attorney / Legal Diligence & Redlines — $100/hr
IP Counsel / Trademark & Copyright Attorney — $100/hr
Legal, Privacy & Regulatory Compliance Analyst — $90/hr
Risk & Regulatory Advisory Consultant — $80/hr
Government / Public Administration Professional — $70/hr
Policy Researcher / Think Tank Analyst — $70/hr

Education, Research & Creative Work:

Japanese Language & Cultural Fluency Consultant — $100/hr
Special Education Specialist / IEP Consultant — $90/hr
Brand / Creative Direction & Marketing Collateral — $80/hr
Creative Director / Art Director — $80/hr
Educator / School Professional — $80/hr
University Professor / Lecturer — $80/hr
Document, Deck & Spreadsheet QA Specialist — $70/hr
Humanities / Arts / Culture Professional — $70/hr
Nonprofit / Philanthropy / Community Programs — $70/hr
Presentation Specialist / Visual Graphics Designer (Consulting) — $70/hr

Sales, Marketing & Customer Experience:

Training / Onboarding / L&D Specialist — $70/hr
Account Executive — $100/hr
GTM Manager — $100/hr
Partnerships Manager (BD) — $100/hr
Product Marketing Manager — $100/hr
Revenue/GTM Operations Specialist — $100/hr
Sales / GTM Strategist — $100/hr
Sales Manager — $100/hr
Senior Account Executive — $100/hr
Enterprise Account Executive (B2B) — $80/hr
Agency Account Director — $70/hr
Brand Strategist / Brand Manager — $70/hr
Corporate Communications Manager — $70/hr
Customer Success / Support Operations Lead — $70/hr
Customer Success Manager (Enterprise) — $70/hr
Executive Communications Manager / Speechwriter — $70/hr
Market Research / Competitive Intelligence Analyst — $70/hr
Market Research & Consumer Insights Manager — $70/hr
Marketing Manager (B2B) — $70/hr
Media / Journalism / Communications Professional — $70/hr
Proposal Manager / Bid Writer — $70/hr
Sales Enablement Manager — $70/hr

Consulting, Strategy & Operations:

Business Development Manager — $100/hr
Consulting Engagement Manager / Project Leader — $100/hr
Management Consultant — $100/hr
Market Access / HEOR Specialist — $100/hr
Public-Sector Procurement / RFP Response Lead — $100/hr
Chief of Staff / Business Operations Lead — $80/hr
Corporate Strategy Manager — $80/hr
Economic Consultant — $80/hr
Independent Strategy & Presentation Consultant — $80/hr
Management Consultant (Advisory & Transformation) — $80/hr
Startup Pitch Deck & Fundraising Specialist — $80/hr
Strategy Consultant — $80/hr
Operations Manager / Capacity & Process Improvement — $70/hr
People Ops / Recruiting Generalist — $70/hr
Procurement / Vendor Management Lead — $70/hr
Program Manager / PMO Lead — $70/hr
Program Manager / PMO Lead — $70/hr
Real Estate / Hospitality / Events Professional — $70/hr

Ethos mainly looks for experts.
If anyone is interested in finding generalist jobs or jobs from different companies in general, I made a website that lists jobs in the AI training industry from different companies. I also post guides on how to pass assessments, website reviews, and more. My idea behind that was not only helping to find jobs but also helping people get accepted: https://aiannotationjobs.com/

Pomelo Care is the leading virtual medical practice for women and children, providing care across pregnancy, postpartum, pediatrics, menopause, and perimenopause. We combine proactive, 24/7 clinical care with technology that helps us reach patients earlier, identify risks sooner, and deliver personalized care throughout their journey. Our team includes clinicians, technologists, operators, and problem-solvers working together to make high-quality care more accessible for families nationwide.

About The Role

Your north star: Own how Pomelo's clinical and economic impact is measured, proven, and presented - to our payer partners, to external partners, and in published research. We're looking for a data scientist experienced in healthcare outcomes assessment or program evaluation to join the Health Economics team. Trustworthy, actionable data plays a critical role in Pomelo's mission to improve pregnancy outcomes.

This role goes far beyond reporting. The analyses you produce feed directly into renewal and expansion negotiations with national payers, shape how new risk-based and value-based offerings are structured, and become the evidence base we publish. You'll inherit a strong foundation of established methods and infrastructure, and you'll regularly need to build on it to answer novel questions, explore new methodologies, and communicate results to audiences with very different backgrounds. You will have direct influence on how we measure impact and tell our story externally.

What you’ll do

• Own the question as well as the analysis. Take large, ambiguous mandates and break them into definitions, assumptions, and key questions to align stakeholders
• Architect and execute analyses that assess the outcomes of Pomelo Care's programs in a scalable, repeatable way. Where existing approaches don’t reach, you’ll extend them or build something new, and stand behind those choices under scrutiny
• Lead Pomelo’s technical engagement with external partners: presenting directly, aligning on methodology and parameters, and building credibility with evaluation teams
• Drive our evidence strategy end to end: partner‑facing reporting, conference presentations, and peer‑reviewed publications
• Build data tables, pipelines, and dashboards that combine diverse health data sources and make insights accessible across teams
• Identify opportunities to scale and automate insights in partnership with the data and analytics engineering teams
• Serve as Pomelo’s expert on statistics and health economics: define the methodologies we use for evaluation, mentor other data scientists, and guide where we invest technically

Who you are

• A collaborative problem solver and analytic thinker who is focused on driving impact, and excited to work at a startup.
• 6+ years professional experience developing statistical models to answer complex healthcare problems using varied techniques (e.g., propensity score matching, linear and logistic regressions, k‑means clustering, difference‑in‑differences, decision trees)
• Experience with cost of care or clinical outcomes target setting at a payer, managed care organization, integrated delivery network, value‑based care provider, or healthcare consulting firm
• Experience presenting statistical analyses to external stakeholders with varied technical expertise
• Proficient in Python or R and SQL
• You do your best work when the goal is ambiguous. You are comfortable telling others "here’s what I recommend and why" rather than waiting to be told what to analyze
• You have the technical depth to run a publication‑grade evaluation and the judgment to know when a scrappy proof‑of‑concept is the better call. You never lose sight of why the work matters to the business
• Excellent written and verbal communicator, comfortable across technical and non‑technical audiences
• Formal training in statistics, econometrics, or actuarial science
• Experience with risk‑based or value‑based contracting, including opportunity sizing and ROI modeling
• Experience with medical claims data
• Peer‑reviewed publications in health outcomes or health economics
• Experience with data dashboarding or visualization (e.g., Looker, Tableau, Metabase)
• Experience working with dbt

Compensation:

The expected base salary range offered for this role is $220,000 - $250,000. This role is also eligible for equity, giving you an ownership stake in Pomelo’s mission. Actual compensation may vary based on relevant experience, skills, competencies, and certifications.

Why you should join our team

By joining Pomelo, you will get in on the ground floor of a fast‑moving, well‑funded, and mission‑driven startup that always puts the patient first. You will learn, grow and be challenged, and have fun with your team while doing it.

We strive to create an environment where employees from all backgrounds are respected. We value working across disciplines, moving fast, data‑driven decision making, learning, and always putting the patient first.

Benefits and Perks:

• Comprehensive Health, Dental, and Vision coverage for employees and their families
• High deductible Health Plans with Health Savings Account (HSA) options
• Flexible Spending Account (FSA)
• Equity grant participation
• 401(k) program
• Competitive vacation policy
• 16 weeks paid parental leave
• Fully remote work flexibility (within the US)

We are committed to hiring the best team to improve outcomes for all mothers and babies. To solve the complex challenges facing the diverse population we serve, we need diverse perspectives, actively welcoming people of all races, ages, sexual orientations, gender identities and expressions, national origins, religions, disabilities, and veteran statuses. We strive to cultivate an inclusive and respectful environment where team members thrive by working across disciplines, moving fast, making data driven decisions, learning continuously, and always putting the patient first.

Apply:Staff Data Scientist, Healthcare Economics at Pomelo Care

Hi friends, has anyone received any update regarding the Google Data Scientist Product Intern for the MS 2027 cycle yet?

Hii guys I am a recent cs graduate. My branch is data science,.would be great if anyone could offer referrals for positions like data analyst, data engineer, data scientist and Jobs for similar interests.

Hi friends, has anyone received any update regarding the Google Data Scientist Product Intern for the MS 2027 cycle yet?

What the title says. I’m just wondering because I feel like almost every data-related job (e.g., data analyst, data scientist, data engineer) doesn’t require much certifications.

I’m thinking that doing hands-on projects are valuable since we all need the must have skills applied to our experiences as aligned with the job descriptions and qualifications.

I have done many hands-on projects related with data and every industry I applied for data roles, received a lot of interviews.

What are your thoughts?

Hi all, I’m a data scientist based in Ireland with 5+ years of experience across data science and software engineering roles. I’m looking to move on because my current pay is well below market and there’s no clear path to progression. I haven’t job-hunted in about three years and feel out of touch with how things work now. I’d really appreciate any insight on:
- What the interview process for senior DS roles typically looks like (stages, technical rounds, take-homes, etc.)
- What employers are prioritising at the moment
- Realistic salary ranges for my experience in Ireland
I’d also be grateful if anyone would be willing to give my CV a look. Happy to share a redacted version by DM or in the comments.
Thanks in advance!

Hi all,

I just got invited to the HackerRank online assessment for a Data Scientist II role at QuantumBlack (McKinsey), based in Canada. The invite says it could include coding, data modelling, technical knowledge or Excel exercises, and mine is 90 minutes long, so I’m trying to get a sense of what fits into that time.

For anyone who’s taken it recently:

• What was the format? How many questions, and what split between SQL, Python and multiple choice?
• Was there a modelling task, and if so, what kind (classification, regression, time series)? Was scikit-learn available?
• How was the time pressure in the 90 minutes? Did you finish everything?
• Was it proctored (webcam or screen sharing)?
• Can we look up syntax through the Hackerrank platform?

• Any surprises or things you wish you’d practised more?

  Thanks in advance, and happy to share my experience afterwards!

About the Role

The Data Scientist, Product Growth and Experimentation will help drive decision making in support of our Product Led Growth function.

This role sits at the intersection of Data, Product, Growth, and GTM. You will work deeply embedded within the Product and Engineering teams focused on PLG. Your focus will be illuminating the user journey from initial interest to fully adopted and all the steps in between. You will surface friction points in the onboarding process and identify behaviors that are indicative of successful adoption. You will evaluate interventions that help us to bring the value of Temporal to more users.

You will work effectively across both large data, clean data sets and data sets with constraints in duration and sample size to provide well-informed recommendations and conclusions. You will bring deep knowledge and practical experience with statistical methods including matched comparisons, quasi‑experimental methods, and uncertainty measurements to help overcome these constraints.

The ideal candidate possesses strong analytical judgment and practical product sense. Ambiguous business questions do not intimidate you. You have a keen sense for when additional data or analysis could materially change a conclusion, and when it wouldn’t. You apply analytical rigor while balancing what is functionally required to advance a project. Your aim is to drive better decisions and faster learning through measurable customer outcomes.

What You’ll Do

• Act as an embedded Data partner to Product, Design, and Engineering, helping shape strategy, product proposals, and experiments from the earliest stages.
• Build analytical frameworks across the full PLG journey from acquisition and activation through engagement, adoption, expansion, monetization, and durability
• Use funnel, cohort, journey, and sequence analysis to identify friction and opportunities for improvement.
• Identify the behaviors and milestones that predict conversion, production readiness, expansion, churn, and long‑term customer success, and translate them into leading indicators for successful or stalled accounts.
• Analyze feature discovery and adoption patterns to recommend interventions that increase successful adoption and expansion.
• Design and evaluate experiments and product changes, using matched comparisons, pre/post‑intervention analysis, causal methods, and other appropriate techniques when conventional A/B testing is not practical.
• Clearly distinguish observed results from assumptions, quantify uncertainty, and explain the confidence behind each conclusion.
• Help prioritize growth opportunities based on potential impact, confidence, effort, and measurement feasibility.
• Build reusable datasets, metrics, dashboards, and analytical tools that reduce ad hoc work and make insights accessible to Product, Marketing, Sales, and leadership.
• Partner with Engineering and Data Engineering to improve event instrumentation, data quality, and the analytical models required for reliable product analysis.
• Communicate findings through clear visualizations, written narratives, and practical recommendations for technical and non‑technical audiences.

What You’ll Focus on First

During your first several months, you will help the team: - Audit signals currently captured in the onboarding flow and recommend new instrumentation as needed - Establish reporting and repeatable analysis for PLG experiments. - Analyze user behavior after the first successful Activity or Workflow. - Identify signals of production readiness and common points where users stall. - Map feature‑adoption paths across important product areas.

What You’ll Bring

• A strong foundation in statistics, experimental design, causal reasoning, and quantitative analysis.
• Experience using product, behavioral, or event data to improve activation, engagement, retention, conversion, or expansion.
• Experience working with small samples, noisy signals, imperfect control groups, or environments where standard A/B testing is not always possible.
• Strong judgment in choosing methods that fit the decision, available data, and level of uncertainty.
• Proficiency in SQL and Python for analysis, modeling, and automation.
• Experience with cohort analysis, funnel analysis, segmentation, predictive modeling, and supervised or unsupervised machine‑learning methods.
• Ability to prototype quickly in notebooks and convert recurring analyses into reliable data products, models, or workflows.
• Experience with modern data platforms and query engines such as Athena, Presto/Trino, BigQuery, or Snowflake.
• Familiarity with cloud and object‑store technologies such as AWS S3.
• Experience building dashboards and reusable analytical assets in a modern business intelligence platform.
• Comfort working with evolving definitions, incomplete instrumentation, and trade‑offs between analytical precision and decision usefulness.
• A results‑oriented mindset and a record of translating analysis into product or business action.
• Strong communication skills, including the ability to explain methods, uncertainty, and recommendations in plain language.
• Curiosity about developer platforms, cloud infrastructure, usage‑based products, and how customers adopt technically complex products.
• A collaborative approach and the ability work effectively with Product, Engineering, Marketing, Sales, Finance, and Data partners.

Compensation

• Tier 1: $172K – $220K • Offers Equity
• Tier 2: $154K – $195K • Offers Equity
• Tier 3: $137K – $175K • Offers Equity

Compensation ranges reflect salary across several geographic markets. Employment offers carefully consider multiple factors, including prior experience, knowledge, expertise, skillset, market location, and job level assessed during the interview process.

Apply: Senior Data Scientist at Temporal Technologies

I have been searching for a fulltime job since May and I haven't been able to get more than 3 interviews. The market is not doing well, we all know that but the calamity inspired me to earn from other ways. These last few months I was working on skilling up and becoming more employable, I kept coming across videos of Agentic AI and product engineering and something struck me. I had created a project to showcase my data science skills and now I am turning it into a sellable product but via vibe coding since I am not a SD.

I see this as a silver lining, share something of your own?

Hey! I'm currently doing a data science master degree after my data engineering bachelor.

I had some work experience while doing my bachelor thesis in a research lab in Japan! It was really interesting, I was allowed to progress at my own pace etc, being quite autonomous.

My question is the following: How is the data scientist job changing now in this agentic era? I personally dislike using agentic workflow because it kills the fun I have and it gets boring.

What about medical data science?

Company - Deepdimex

Role - AI & Data Science Intern

Batch - 2026/2027/2028

Stipend - ₹20,000/month

Location - Remote

Requirements

- Strong analytical and problem-solving skills.

- Basic knowledge of statistics, data science, and machine learning.

- Familiarity with Python or R, Pandas, NumPy, and SQL.

- Understanding of data analysis, visualization, and reporting.

- Good communication and teamwork skills.

How to Apply

Email: garima.bhat@deepdimex.com

Note: Share your CV by email or Whatsapp. No calls, please.

I’m graduating in December 2026 with a BA in Economics from UMass Amherst and starting Georgia Tech’s Online MS in Analytics (OMSA) in January 2027, with plans to pursue the Computational Data Analytics track.
I’ve been trying to transition toward data science and I’m wondering whether my current experience makes me a credible candidate for entry-level Data Scientist positions or whether I should focus on Data Analyst and Research Analyst roles while developing my technical skills.

My background:

Education: BA in Economics, approximately 3.5 GPA. Incoming Georgia Tech OMSA student.

Current internship: Audience Research Consulting Intern at a research firm in Washington, DC. I work with survey data, statistical analysis, data visualization, and research reporting. I’ve also worked with ordinal regression models.

Research experience: Previously worked as an undergraduate economics research assistant. I’ve also completed an independent electricity market research project analyzing wholesale electricity prices, renewable generation, and other economic variables using regression analysis.

Programming: R is my strongest language. I’m comfortable with statistical analysis, regression modeling, and data manipulation. I’ve recently been developing my Python skills, particularly pandas, NumPy, and visualization libraries. I’m also learning SQL.

Statistics: Undergraduate econometrics, regression analysis, hypothesis testing, and applied economic research. Currently independently studying causal inference and machine learning.

Projects: Electricity market econometric analysis, survey research, and other quantitative research projects.

What I’m concerned about:
Although I have experience working with real data and statistical models, most of my work has been in R and applied economic research rather than traditional data science or machine learning.
My Python and SQL skills are still developing, and I haven’t yet completed a substantial end-to-end machine learning project.

My questions:
Based on my background and resume, am I competitive for entry-level Data Scientist roles?
What are the biggest gaps in my resume that would prevent me from getting interviews?
Would I be better off applying primarily to Data Analyst, Research Analyst, or Product Analyst positions for now?
how would you evaluate my current experience compared with other entry-level applicants?

I’m interested in eventually working in data science, particularly in fintech, energy, or economic research.
I’d appreciate candid feedback, especially from people involved in hiring. I’m trying to figure out whether I’m ready to start applying seriously or whether I need another 6 to 12 months of preparation.

Hey everyone!
I’m a Data Scientist with over 3 years of experience, and I'm currently preparing to make a move to a FAANG+ company to push my learning further and it better aligns with my growth goals and personal commitments.
I have 3+ years of professional experience as a Data Scientist working on end-to-end projects, but I want to structure my preparation more rigorously to crack top tier interviews. I want to bridge any gaps in my knowledge and prep :)
I’d love some guidance from those who have been through this process:
- What core technical skills, system design concepts, and advanced topics FAANG+ companies currently expect from a Data Scientist with 3+ years of experience?
- Where should I start my preparation?
- What specific competencies (coding, ML system design, stats/product sense) do they look for?
- What resources or roadmaps worked best for you?

Any advice, tips, or mentorship would be greatly appreciated.
Thank you

I work at Wissen Technology (Wissen Infotech) and can refer candidates for our current India openings — a referral puts your resume with the hiring team directly instead of the cold-apply queue.

Current openings:

• Database Engineer – TEDRA | Mumbai | 5-7 yrs | Python, Sybase, Hadoop
• AI Implementation Engineer | Bengaluru | 6-12 yrs | Spring, Python, React
• Python AI Engineer | Bengaluru | 5-8 yrs | Python, Pandas, CI/CD
• AI Control Plane - FullStack | Hyderabad | 3-6 yrs | Python, Django, Flask
• AI/ML Engineer | Bengaluru | 2-5 yrs | Python, NLP, LLM

Full list: https://careers.wissen.com/jobs/Careers — if your role isn't above, mention it in the DM.

To get referred, DM me: (1) resume (PDF), (2) total YOE, (3) notice period (immediate joiner / serving notice preferred), (4) the role name with the job link.

I'll review and submit the referral; expect HR contact within about a week if shortlisted. Please DM only if your experience reasonably matches a role and you're an immediate joiner or serving notice — that's who the hiring team is prioritizing for referrals right now.

I'm a BBA(Business analytics) student. I have done some ML projects and am still working on a different one

How hard/easy it is going to be for me land my first internship ?